iot

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What is Message Queue Telemetry Transport (MQTT)? How to secure MQTT?
MQTT is a messaging protocol broadly used in IoT and connected services, very lightweight and reliable even over poor quality networks. It is designed lightweight so it can work on constrained devices but, even in its latest version MQTTv5, the attack surface is very large.
Fouad_Chmainy
Jan 30, 2025 Place Technical Articles
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Security for IoT Devices and Why It’s Important
IoT We do use Personal Computers (PC) and server/client computers that run Windows, Linux, etc. PCs are used for helping human activity, thus the computer network is basically for displaying/output info/video/audio to humans and input by humans, so it is Human to Human (H2H) network. When we talk about CyberSecurity, that refers to those server/client PCs and TCP/IP security. Other than PC,s there are Micro Computers/Embedded Computers that are used for Home Electronics, Factory machines, live cameras, or small devices. Most of them were used to work for in-house tasks and were not connected to the Internet with TCP/IP protocol until recently. By the way, I think the iPhone is the most successful computer device that uses the Internet in the history of computers. However, the iPhone (and iPod touch) is not the first handheld device of Apple. Apple released the “Newton” in 1993 which can perform a variety of tasks like the iPhone. However, the sale of the Newton was not good and the project was canceled. We are not concerned here with the question of Newton's failure, however, what the iPhone has and what Newton hasn't - is the ability to connect to the Internet. As a result of the mass production of iPhone and other smartphones, microcomputers, GPS receivers, and small sensor devices became inexpensive and mass-produced, and Internet connectivity became possible with inexpensive components. Naturally, Micro Computers/Embedded Computers are combined with cheap network access devices - the combination of these microcomputers and networks is called Internet of the Things (IoT). In most cases, IoT devices relay data from sensors which is attached to the IoT devices, and it relays to other IoT devices to aggregate the data for processing – the IoT devices are connected, and the communications are done among IoT (machines): so it is Machine to Machine (M2M) network. So the IoT devices are also to be M2M network devices. One of the well-known examples of IoT devices is the Arduino board which is an open-source electronics platform based on easy-to-use hardware and software. Arduino is easy to program, and deploy, and can use many types of sensors, and the cost is quite low, thus it has been used in thousands (or more) of projects and applications. As IoT devices are much cheaper and easier to produce compared to the PC, the number of IoT devices increases rapidly, and no limitation on the producing number. In contrast, the demand for PCs (and smartphones) is limited by the number of humans. The number of IoT devices that are connected (cite from statista) 2019 8.6 billion 2023 15.14 billion As the number of IoT devices increases, the network connecting IoT devices (M2M) increases geometrically. By the way, BigIP LTM has a profile to use one of the protocols which is used for IoT networks ( Local Traffic ›› Profiles : Services : MQTT ). Security Concerns What problems will arise from IoTs? Attack surface First, unlike servers and PCs, these IoT devices are small and can be transported anywhere (laptop PC is portable, but limited to the space where human goes). A good example is drones – which has microcomputers and network connecting devices thus IoT - that can move autonomously from place to place, even to the place humans can’t go. Therefore, they are not restricted access by physical location and can be connected to the Internet wherever they are located. Therefore, unlike servers and PCs, it is difficult to know the location of all IoT devices in the world. The problem is that IoT devices are directly accessible by malicious attackers: they can be everywhere and the number of devices are too many to track all of them. From the network perspective, servers and PCs are always protected because they have limited physical access points = Attack Surface, and even if they become the source of an attack, the locations of the malicious attacker’s host can be determined to some extent. The CVSS metrics score low when the PC/Servers are not accessible via the network. In contrast, since it is hard to know all the locations of IoT devices and their M2M network connection points, the Attack Surface is everywhere. If an IoT device that is located in an unknown (physical) place is compromised and becomes a jump host, it might be difficult for a defender to know where the attack is coming from. In other words, being everywhere because it is convenient also means not knowing where they are. We need to think about expanding the attack surface. You may recall the Mirai botnet - Mirai's primarily targets IoT devices such as IP cameras and home routers - IP cameras can be placed on the outside of the building so easy to access for the malicious attacker. In the Keynote speech of BlackHatAsia 2019, the presenter of the speech said that “IoT is next asbestos!” Not only physical access, the range of the network is going to be expanding. As the number of network devices increases, the amount of network connecting them also increases geometrically, so the network that needs to be monitored will also expand. Network protocol Second, many IoT devices use protocols other than TCP/IP. Since they were used in the closed network before the IoT era like in the factory or car, the design and implementation of such protocols do not need to consider security and privacy. However, once it connects to the Internet, attacks against them are often easy due to the nature of those protocols, which are not security-conscious, and the lack of research that has been done on them may make these attacks possible. For example, the CAN network is used for in-vehicle (i.e. car) networks, which have no destination or source address. Therefore, it is difficult to identify and block the source of an attack through the CAN network. Some IoT devices communicate through TCP/IP and HTTP protocol, but not HTTPS – it is because those devices are designed to be using small memory and narrow network bandwidth. Of course, it is not secure. The amplified DDOS attack As mentioned above, the number of the PC is limited while the IoT devices are limitless. And the protocol has some security weaknesses – so the IoT devices could be compromised and used as jump hosts for DDOS campaigns. The jump hosts which is used for the DDOS attack will be amplified - more than that of the H2H network, and it make it difficult to defend. Mirai botnet is one of the most famous IoT attacking bots. Quote from What was the Mirai botnet? "In late 2016 in France, telecom company OVH was hit by a distributed denial-of-service (DDoS) attack. Experts were struck by how the assault was 100 times larger than similar threats." This incident happened in 2016 - as shown above, we have more and more IoT devices. Defense IoT devices behave differently than PC/Servers and require their own cybersecurity rules depending on how they operate. To reduce the risks of IoT devices, some system standards and security guidelines for IoT have been published by governments and non-profit organizations. USA IoT Cyber Security Improvement Act of 2020 https://www.govinfo.gov/content/pkg/COMPS-15863/pdf/COMPS-15863.pdf NIST IoT Device Cybersecurity Guidance for the Federal Government https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-213.pdf USA DHS : Strategic Principles for Securing the Internet of Things https://www.dhs.gov/securingtheIoT IEEE IoT security best practices white paper https://standards.ieee.org/wp-content/uploads/import/documents/other/whitepaper-internet-of-things-2017-dh-v1.pdf To mitigate the risk, IoT devices need to consider implementing security measures when it is designed. For example, access control feature and user(machine) authorization to change the config, implement encryption (while it is a performance trade-off), monitor the abnormality, and use Edge computer to filter the data and proxy the connection. And, of course, not using default user/Password is essential – the Mirai botnet will use them. In most cases the data from IoT devices will be uploaded to cloud service and processed on the application layer – thus application firewall can be one of the protection measures. Future Think about the future – the number of IoT devices, the M2M network, and the amount of data on the M2M network will be exponentially increased, thus humans might be overwhelmed to monitor and analyze the network. Recently generative AI has been used for large amounts of data, so AI will also be used for IoT security. As discussed in another article, the security of AI is also important, and, if AI and IoT are united, things need to be considered might be more. Further study Thesis of IoT security in arxiv: A Survey of the Security Challenges and Requirements for IoT Operating Systems https://arxiv.org/abs/2310.19825 A Unified Taxonomy and Evaluation of IoT Security Guidelines https://arxiv.org/abs/2310.01653 Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future https://arxiv.org/abs/2309.02707 A Large-Scale Study of IoT Security Weaknesses and Vulnerabilities in the Wild https://arxiv.org/abs/2308.13141 Unleashing IoT Security: Assessing the Effectiveness of Best Practices in Protecting Against Threats https://arxiv.org/abs/2308.12072 IoT and Man-in-the-Middle Attacks https://arxiv.org/abs/2308.02479 5G Networks and IoT Devices: Mitigating DDoS Attacks with Deep Learning Techniques https://arxiv.org/abs/2311.06938 IoT in the Era of Generative AI: Vision and Challenges https://arxiv.org/abs/2401.01923
Koichi
Mar 14, 2024 Place Technical Articles
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The Internet of Sports
Did you see what the NFL is doing this year with sensors? Earlier this month they announced a partnership with Zebra Technologies, a company that provides RFID chips for applications from 'automotive assembly lines to dairy cows' milk production.' This season there will be sensors in the player's shoulder pads which will track all their on field movements. This includes player acceleration rates, top speed, length of runs, and even the distance between a ball carrier and a defender. Next year they'll add sensors for breathing, temperature and heart rate. More stats than ever and could change the game for-ever. Imagine coaches being able to examine that data and instantly call a play based on it. Play by play. To me it somewhat takes away that 'feel' for the game flow but also having data to confirm or deny that feeling might make for exciting games. Maybe lots of 0-0 overtimes or a 70-0 blowout. Data vs. data. Oh how do I miss my old buzzing electric football game. The yardsticks will have chips along with the refs and all that data is picked up by 20 RFID receivers placed throughout the stadium. Those, in turn, are wired to a hub and server which processes the data. 25 times a second, data will be transmitted to the receivers and the quarter sized sensors use a typical watch battery. The data goes to the NFL 'cloud' and available in seconds. The only thing without a sensor is the ball. But that's probably coming soon since we already have the 94Fifty sensor basketball. And we've had the NASCAR RACEf/x for years and this year they are going to track every turn of the wrench with RFID tracking in the pits and sensors on the crew. Riddell has impact sensors in their helmets to analyze, transmit and alert if an impact exceeds a predetermined threshold. They can measure the force of a NBA dunk; they can recognize the pitcher’s grip and figure out the pitch; then the bat sensor that can measure impact to the ball, the barrel angle of their swings, and how fast their hands are moving; and they are tracking soccer player movement in Germany. Heck, many ordinary people wear sensor infused bracelets to track their activity. We've come a long way since John Madden sketched over a telestrator years ago and with 300 plus lb. players running around with sensors, this is truly Big Data. It also confirms my notion that the IoT should really be the Internet of Nouns - the players, the stadiums and the yardsticks. ps Related: Player-tracking system will let NFL fans go deeper than ever Fantasy footballers and coaches rejoice—NFL players to wear RFID tags More sensors are coming to professional sports, but research outpaces business models Why This Nascar Team Is Putting RFID Sensors On Every Person In The Pit Impact Sensors: Riddell InSite Impact Response System Fastpitch Softball League Adds Swing Sensors to its Gear Technorati Tags: rfid,sensors,IoT,things,nfl,cloud,big data,silva,f5 Connect with Peter: Connect with F5:
PSilva
Mar 16, 2023 Place Technical Articles
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F5 BIG-IP MQTT protocol support and use cases in an IoT environment
The Internet-of-Things is a system of physical devices, vehicles, buildings, and any other items each provided with a unique identifier allowing them to communicate with one another without any human intervention. MQTT is a widely-used machine-to-machine connectivity protocol that helps these devices communicate and exchange messages. The wide adoption and popularity of the MQTT protocol led to its support in the BIG-IP version 13.0. MQTT is a publish/subscribe messaging protocol. A device such as a camera, heat sensor, lP-enabled light bulb, etc. can publish data to an intermediary module using the MQTT protocol. An application can then subscribe to this intermediary module and retrieve the published data. Intermediary modules are also known as message brokers. The BIG-IP with MQTT awareness can sit in front of the MQTT message brokers to provide scalability, security, visibility, and availability. Fig. 1 – Basic architecture of using the BIG-IP platform in an IoT environment. In an MQTT configuration, clients publish messages and the BIG-IP system parses those MQTT messages based on which it invokes MQTT specific iRule events if defined and performs connection based load balancing on the MQTT messages to a pool of message brokers. The message brokers then transport and route the messages to subscribing servers A typical BIG-IP MQTT configuration includes: MQTT pool of message brokers Are grouped together to receive and process traffic. After the pool is created, associate the pool with a virtual server. Some common open source message brokers examples are Mosquitto and VerneMQ iRules for MQTT Use iRules to exercise MQTT functionality, for example to log the messages that the BIG-IP system passes, or to pass the client certificate's common name in the CONNECT message Client SSL profile Use a Client SSL profile when you want the BIG-IP ® system to authenticate and decrypt/encrypt client-side application traffic Virtual server configured to use MQTT functionality For more details please refer to: https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/ltm-iot-administration-13-0-0/1.html BIG-IP natively supports the MQTT protocol. BIG-IP has a full proxy architecture which makes BIG-IP itself an endpoint and an originator of the MQTT protocol. iRules take advantage of the deep understanding of the protocol and can be used at different events (specific moments within the session flow of a network connection, such as MQTT_CLIENT_INGRESS, MQTT_SERVER_INGRESS) to intelligently parse the MQTT protocol and make traffic decisions. Let’s explore some of the use cases using iRules such as load balancing and steering traffic based on a unique identified present within the MQTT protocol, preventing attacks based on TOPICS/LENGTH of a PUBLISH message, client authentication based on CN name present in the client certificate. Use Case: prevent MQTT DDoS attacks based on the below parameters Topic validation Validate the ‘TOPIC’ of a PUBLISH message and if it does not fit the validation criteria then drop the connection. This will prevent messages with bogus TOPICS from reaching the message brokers. And help in preventing MQTT DDoS attacks based on TOPIC. when MQTT_CLIENT_INGRESS { log local0. "CLIENT [MQTT::type]" if {[MQTT::type] eq "PUBLISH" } { # Check against a allowed topic. if { [MQTT::topic] eq "bogus/bogus" } { # Invalid topic log local0. " Topic is Invalid. Potential DDoS Attack -> Dropping Topic: [MQTT::topic]" drop } } } The above iRule can be enhanced to use data groups where the data groups will have the entire list of TOPICS and the [MQTT::TOPIC] can be checked against the data group MQTT PUBLISH message length validation An application will typically have knowledge about the size of the data that is being transmitted. Taking advantage of that knowledge the length of a PUBLISH message can be validated and if it does not satisfy the expected length then drop the connection. This will prevent large messages from reaching the message brokers and not overload the broker. when MQTT_CLIENT_INGRESS { log local0. "CLIENT [MQTT::type]" if {[MQTT::type] eq "PUBLISH" } { # Check length of message. if { [MQTT::length] > 100 } { # Invalid length log local0. " Length is Invalid. Potential DDoS Attack -> Dropping message: [MQTT::topic] : [MQTT::length]" drop } } } Use Case: pool selection/load balancing based on username as a unique identifier Use the username as a unique identifier to steer traffic to a message broker. This enables stickiness between an end user and a message broker by mapping a device/end user to a pool in the load balancer. The mapping helps in conditions where in a device needs to reconnect to the message broker on which the active client session lives and can use the state information present on the message broker to make decisions. when MQTT_CLIENT_INGRESS { log local0. "CLIENT [MQTT::type]" if {[MQTT::type] eq "CONNECT" } { # Select pool based on username, example license ID if { [MQTT::username] eq "D1111111" } { log local0. "Load balancing to pool MQTT-BrokerPool1" pool MQTT-BrokerPool1 } if { [MQTT::username] eq "D1111112" } { log local0. "Load balancing to pool MQTT-BrokerPool2" pool MQTT-BrokerPool2 } } } The above iRule can be enhanced to use data groups where the data groups will have the list of unique usernames. Multiple data groups can be defined, each one representing users for multiple Pools. The [MQTT::username] can be checked against the data group and based on that the pool selection can be made. Use Case: client certificate authentication over TLS BIG-IP can terminate MQTT encrypted SSL/TLS messages and then send the un-encrypted traffic to the backend Broker. This allows the Broker to scale as it can offload all SSL/TLS functions and configuration to the BIG-IP. In addition to terminating SSL/TLS the BIG-IP can use iRules to perform Client Certificate Authentication. The BIG-IP can embed the client CN name from the client certificate into the backend connection along with the username for authentication by the back-end Broker. when CLIENT_ACCEPTED { set cn "" } when CLIENTSSL_CLIENTCERT { log local0. " Parsing X509 Info for SSL Client Cert CN Name" set cn [findstr [X509::subject [SSL::cert 0]] "CN=" 3 ","] log local0. "Found Client Cert Common Name (CN) : $cn" } when MQTT_CLIENT_INGRESS { log local0. "MQTT Client MmessageTtype [MQTT::type]" if {[MQTT::type] == "CONNECT"} { log local0. "Connecting to Broker" if {$cn == ""} { # if we didn't see a client cert, return an authentication error MQTT::drop MQTT::respond type CONNACK return_code 5 MQTT::disconnect } else { log local0. "Passing Username and CN to Backend for Authentication" log local0. "MQTT Username: [MQTT::username]" log local0. "Username: [MQTT::username] CN: $cn" set mqttuser [MQTT::username] MQTT::username "$mqttuser $cn" } } } Conclusion Bookmark this page if you are interested in learning more. We will be update this blog with new compelling IoT features developed by F5 for the upcoming BIG-IP releases. Do you have a suggestion for an IoT related topic that you would like for us to cover? Please leave a comment on this post if you do. References https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/ltm-iot-administration-13-0-0/1.print.html https://devcentral.f5.com/s/articles/lightboard-lessons-iot-on-big-ip-24923?tag=lbl https://devcentral.f5.com/s/articles/the-iot-ready-platform https://f5.com/resources/white-papers/tmos-redefining-the-solution https://devcentral.f5.com/s/articles/the101-irules-101-events-amp-priorities https://en.wikipedia.org/wiki/MQTT https://mosquitto.org/
Payal_S
Sep 17, 2019 Place Technical Articles
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Lightboard Lessons: Exploiting Cellular IoT Gateways
Critical emergency services such as police, fire, and medical manage their fleets with vulnerable cellular IoT devices. “Vulnerable” doesn’t have to mean a vulnerability within the hardware or software, although we suspect that is the case in some makes and models. In this instance, "vulnerable" can mean being susceptible to remote attacks because of weak access control and use of default credentials. An attacker can use these vulnerable device to launch attacks, as we have seen with thingbots like Mirai and Reaper, or they can use that access for nefarious purposes to spy, redirect commands in the case of a fleet taking orders from a remote command, or shut the system off, effectively disabling operations. In this video, John outlines the problem of weak authentication in widely-used cellular gateway devices. Help spread the word, and for the love of all things security, change your default usernames and passwords! Related Resources: F5 Labs Report: Breaking Down the Door to Emergency Services through Cellular IoT Gateways F5 Labs Report: Leveraging Government Transparency to Find Vulnerable Cellular Gateways
ltwagnon
Sep 20, 2018 Place Technical Articles
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Post of the Week: Explaining the KRACK Vulnerability
In this "Post of the Week" video, we discuss the KRACK vulnerability that targets mobile devices and wireless routers. This vulnerability targets the WPA2 security protocol that allows for encryption between a mobile device and a wireless router. As the mobile device negotiates encrypted communication with the router, an attacker can force the mobile device to use very weak encryption (essentially no encryption at all) and thus see all the traffic between the device and the router. We also talk about ways you can help avoid this problem. Enjoy! Related Resources New Threat May Slip Through the KRACK in BYOD Policies (F5 Labs) Scary Candy Week: KRACK and ROCA
ltwagnon
Oct 20, 2017 Place Technical Articles
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Lightboard Lessons: Connecting Cars with BIG-IP
I light up how BIG-IP and Solace work together in a MQTT connected car infrastructure. ps Related: Using F5 BIG-IP and Solace Open Data Movement technology for MQTT message routing and delivery Lightboard Lessons: What is MQTT? Solace and F5: Partnering for Better IoT
PSilva
Oct 04, 2017 Place Technical Articles
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Using F5 BIG-IP and Solace Open Data Movement technology for MQTT message routing and delivery
The "Internet of Things" (IoT) has the potential to not just impact the way we live and work, but to disrupt entire industries. Some of the major industries that are driving innovation in IoT include manufacturing, transportation, and utilities. In this post I’ll talk about an example of how digital manufacturing is helping automobiles be more intelligent. There are millions of connected automobiles that have software running on them: from programs that keep GPS maps up to date to sensors sending vehicle speeds or temperature information. This information typically is being sent to a centralized management system that enables intelligent decisions, and those back-end systems also need to send data, instructions, and updates to the cars. We are actively working with a leading multinational automotive company. In this deployment the management system uses MQTT to send notifications to cars that a new software update is available for download. It is critical that these messages are received by the connected cars, but message delivery can be delayed if the car can’t be reached because it’s out of range, or driving through a tunnel, or even if cellular networks are congested. Using the Solace message broker To ensure eventual delivery in such situations, you can have the management system send messages to a message broker that in turn distributes them to intended recipients. This decouples your architecture so the many elements of the management system don’t need to worry about the specific destinations to which each message must be delivered, nor track delivery status. They simply send a message to the broker which A) takes care of routing it to requisite destinations, and B) stores a copy of it until every vehicle that needs it has confirmed receipt. Basic IIoT architecture for connected automobiles Before diving deeper, let’s look at the architecture that is used in the above use case. The idea is the same, but to support the numbers of connected vehicles and volume of data involved, it’s necessary to implement multiple message brokers. This architecture is provided by Solace which uses a novel architecture that enables efficient publish/subscribe distribution of data and can scale to millions of connected devices. (see Fig 1.). Back-end applications connect to a single broker (core message broker) to send a message to any vehicle, and can use messaging techniques preferred by IT applications such as JMS, AMQP and Node.js. The core message broker is communicating to several edge message brokers through internal messaging. The data for a particular vehicle is routed through one edge message broker and delivered to the vehicle in the matter conducive for it, in this case MQTT. In the diagram, Vehicle 1 connects to Message Broker 1. That means that messages sent from the management system to the core message broker that are intended for Vehicle 1 only need to go to Message Broker 1 Fig. 1 – Basic IIoT architecture for connected automobiles This two-tier approach provides a simple and powerful scaling architecture for north-south communication, since more connected cars can be added by adding more edge message routers without affecting the existing system. BIG-IP and persistence For this architecture, we’re aiming to achieve two things: First, we want to relieve the management system of the burden of keeping track of message delivery to potentially millions of vehicles. The Solace message broker uses MQTT QoS Level 1 which guarantees that a message will be delivered at least once to the receiver. The message is persisted in the edge message broker which allows the backend IoT application to publish messages with confidence that they will eventually reach their destination, but without needing to keep track of message delivery status. Second, we need to make sure that the vehicle connects to the right message broker so it can receive its messages. This can be achieved by managing a 1:1 mapping between the edge message broker and the vehicle. Fig. 2 – F5 BIG-IP in the IoT architecture BIG-IP version 13+ helps to achieve the 1:1 mapping with support for MQTT message parsing. It sits in front of the message broker and parses the MQTT messages – using iRules – exchanged between the vehicle to the message broker. Data groups on the BIG-IP are used to map a vehicle using a unique Identifier to a pool of message brokers. Using iRules every MQTT message is parsed, then the data group lookup routes the data to the correct pool of message brokers. This helps to achieve a “sticky” load balancing solution so that when a vehicle comes back online it will always get routed and connected to the correct message brokers where the connection state for that vehicle is known to be maintained. We say a “pool of message brokers” in order for the brokers to provide a highly-available service. Here is some sample code of an iRule that helps with achieving persistence or sticky load balancing: when MQTT_CLIENT_INGRESS { log local0. "CLIENT [MQTT::type]" if {[MQTT::type] eq "CONNECT" } { # Select pool based on vehicle ID if { [MQTT::username] eq "D1111111" } { log local0. "Load balancing to pool MQTT-BrokerPool1" pool MQTT-BrokerPool1 } if { [MQTT::username] eq "D1111112" } { log local0. "Load balancing to pool MQTT-BrokerPool2" pool MQTT-BrokerPool2 } } } Conclusion IoT use cases which benefit from having a guaranteed delivery of messages can take advantage of F5’s persistence capabilities. The architecture described above means that specific edge broker instances will maintain 'state' for specific connected vehicles. This requires the MQTT load-balancing to be sticky across sessions. BIG-IP version 13+ supports MQTT message parsing using iRules and thereby provides a key functionality in achieving the end-to-end goal of the solution for this type of architecture. The industries that are embracing “Internet of Things” applications are still in the early stages of innovation, but market leaders are architecting now for scale and resilience so they can automate more and more processes with a single infrastructure. The automaker in this example has chosen F5’s BIG-IP solution for 1:1 mapping of cars to message brokers, and Solace’s Open Data Movement technology as the MQTT infrastructure for message routing and delivery. The combination provides an elegant solution that can scale to millions of connections to support an increasing number of message exchanges between the vehicles and back end systems as their telematics and in-car services get more sophisticated.
Payal_S
Oct 03, 2017 Place Technical Articles
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What to Expect in 2017: Mobile Device Security
We are mobile, our devices are mobile, the networks we connect to are mobile and the applications we access are mobile. Mobility, in all its iterations, is a huge enabler and concern for enterprises and it'll only get worse as we start wearing our connected clothing to the office. If the last 10 years wasn’t warning enough, 2017 will be a huge year for mobile…again. Every year, it seems, new security opportunities, challenges and questions surround the mobile landscape. And now it encompasses more than just the device that causes phantom vibration syndrome, it now involves the dizzying array of sensors, devices and automatons in our households, offices and municipalities. Mobile has infiltrated our society and our bodies along with it. So the security stakes are high. The more we become one with our mobile devices, the more they become targets. It holds our most precious secrets which can be very valuable. We need to use care when operating such a device since, in many ways, our lives depend on it. And with the increased automation, digitization and data gathering, there are always security concerns. So how do we stay safe? The consumerization of IT technologies has made us all administrators of our personal infrastructure of connected devices. Our digital self has become a life of its own. As individuals we need to stay vigilant about clicking suspicious links, updating software, changing passwords, backing up data, watching financial accounts, having AV/FW and generally locking down devices like we do the doors to our home. Even then, the smartphone enabled deadbolt can be a risk. And we haven’t even touched on mobile payment systems, IoT botnets or the untested, insecure apps on the mobile phone itself. Cybersecurity is a social issue that impacts us all and we all need to be accountable. For enterprises, mobile devices carry an increased risk, especially personal devices connecting to an internal network. From regulatory compliance to the disgruntled employee, keeping sensitive information secret is top concern. BYOD policies and MDM solutions help as does segmenting those devices away from critical info. And the issue isn’t so much seeing restricted information, especially if your job requires it, it is more about unauthorized access if the device is compromised or lost. Many organizations have policies in place to combat this, including a total device wipe…which may also blast your personal keepsakes. The endpoint security market is maturing but won’t fill the ever-present security gaps. From your workforce to your customers, your mobile web applications are also a target. The Anti-Phishing Working Group (APWG) reports a 250 percent jump in the number of detected phishing websites between October 2015 and March 2016. Around 230,000 unique phishing campaigns a month, many aimed at mobile devices arriving as worrisome text messages. Late 2016 saw mobile browsing overtake desktop for the first time and Google now favors mobile-friendly websites for its mobile search results. A double compatibility and SEO whammy. And those two might not be the biggest risk to an organization since weakest link in the security ecosystem might be third-party vendors and suppliers. On the industrial side, tractors, weather sensors, street lights, HVAC systems, your car and other critical infrastructure are now mobile devices with their own unique security implications. The Industrial Internet of Things (IIoT) focuses on industrial control systems, device to network access and all the other connective sensor capabilities. These attacks are less frequent, at least today, but the consequences can be huge – taking out industrial plants, buildings, farms, and even entire cities. The Digital Dress Code has emerged and with 5G on the way, mobile device security takes on a whole new meaning. ps Related: Mobile Trends For 2017 And Beyond Perspectives on Securing Mobile and Social Business, 12 Months On RSAC17: More ransomware and IoT-enabled attacks on the way, warns expert Mobile Malware Milestone Mobile banking and how to stay secure What Does Mobile Mean, Anyway? BYOD - concentrate on the apps, not the devices 10 Security Trends To Watch For At RSA 2017
PSilva
Feb 20, 2017 Place Technical Articles
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Lightboard Lessons: IoT on BIG-IP
As more organizations deploy IoT applications in their data centers and clouds, they're going to need their ADC to understand the unique protocols these devices use to communicate. In this Lightboard Lesson, I light up how IoT protocol MQTT (Message Queuing Telemetry Transport) works on BIG-IP v13. iRules allow you to do Topic based load balancing along with sensor authentication. And if you missed it, here is the #LBL on What is MQTT? ps Related: Lightboard Lessons: What is MQTT? Security Trends in 2016: Securing the Internet of Things The Intruders of Things The IoT Ready Platform Using F5 BIG-IP with IBM MessageSight
PSilva
Feb 08, 2017 Place Technical Articles
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is Message Queue Telemetry Transport (MQTT)? How to secure MQTT?","conversation":{"__ref":"Conversation:conversation:332019"},"id":"message:332019","revisionNum":4,"uid":332019,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:154941"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" MQTT is a messaging protocol broadly used in IoT and connected services, very lightweight and reliable even over poor quality networks. It is designed lightweight so it can work on constrained devices but, even in its latest version MQTTv5, the attack surface is very large. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":311},"postTime":"2024-08-12T05:00:00.031-07:00","lastPublishTime":"2024-08-12T05:00:00.031-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Table of Content \n 1. What is MQTT? \n 1.1. Presentation \n 1.2. Constrained devices \n 1.3. Use Cases \n 1.4. Alternatives to MQTT \n 2. Architecture \n 2.1. Overall Architecture \n 2.2. Terminology \n 2.2.1. Topic \n 2.2.2. Message \n 2.2.3. Subscriber \n 2.2.4. Publisher \n 2.2.5. Broker \n 2.2.6. Who is the Client, who is the Server? \n 2.3. Traffic overview \n 2.4. MQTT Quality of Service (QoS) \n 2.5. Load Balancing of brokers \n 2.5.1. Extend Natively with NGINX \n 2.5.2. Extend with NJS \n 3. MQTT Brokers \n 3.1. Most popular MQTT brokers \n 3.1. Why proxy MQTT traffic? \n 4. MQTT Security \n 4.1. Security Context and Attack surface \n 4.2. IoT devices generally don’t encrypt communication \n 4.3 Authentication and AccessControl \n 4.4. Injections \n 5. How can NGINX enrich your MQTT use cases? \n 5.1. What is NGINX? \n 5.2. Traffic optimisation \n 5.3. MQTT Security \n 5.4. Analytics and Telemetry \n \n 1. What is MQTT? \n 1.1. Presentation \n Message Queue Telemetry Transport (MQTT) is a standard messaging protocol for the Internet of Things (IoT). \n MQTT is designed with a small footprint and a lightweight publish/subscribe messaging transport, which makes it ideal for connecting IoT devices for various use cases, from connecting smart home devices to industrial robots or connected cars. \n Benefits of MQTT \n \n Lightweight : The hardware requirements to run MQTT clients are very small so it can be used on any small microchips. \n Network Efficiency: MQTT messages are small, so it does not require high bandwidth to operate. \n Reliable: Reliability of message delivery is important for many IoT use cases. This is why MQTT has different quality of service levels. \n Support for Unreliable Networks: Many IoT devices connect over unreliable cellular networks. MQTT’s support for persistent sessions reduces the time to reconnect the client with the broker. \n Security Enabled: MQTT has support for message encryption and authentication. We will see in this document that we often make trade-offs on security to keep the lightness of devices. \n \n MQTT Publish / Subscribe Architecture \n \n The current implementation of MQTT is MQTTv5 which brings more scalability, improved features and better error handling than its older brother MQTT v3. \n References: \n https://mqtt.org/ \n \n 1.2. Constrained devices \n When you talk about IoT you directly think about your connected coffee machine, connected toothbrush or sensors hidden everywhere in your apartment. You certainly don’t want to have a computer sized add-on to your devices that consumes more power than the device itself. \n That’s why there is a strong need to have constrained devices that have low power consumption requirements and have a small footprint. However, this also means limited compute performance including security processing. \n There are different classed for constrained devices depending on their RAM and flash requirements which directly impact their power consumption. \n \n \n \n \n \n Classes of Constrained Devices \n \n \n \n \n CLASS \n \n \n RAM Size \n \n \n Flash Size \n \n \n \n \n Class 0, C0 \n \n \n << 10 KiB \n \n \n << 100KB \n \n \n \n \n Class 1, C1 \n \n \n ~ 10 KiB \n \n \n ~ 100 KiB \n \n \n \n \n Class 2, C2 \n \n \n ~50KB \n \n \n ~250KB \n \n \n \n \n \n https://datatracker.ietf.org/doc/html/rfc7228 \n \n 1.3. Use Cases \n When I started looking into messaging protocols and MQTT, I only had 2 use cases in mind: smart homes and connected cars. An example of a smart home use case would be a connected temperature sensor. These tend to be more expensive than traditional thermometers, but it can provide nice graphs on my mobile device and does the conversion between °F and °C automatically. In terms of connected cars, more and more vehicle manufacturers offer remote telemetry, mobile device connectivity and data-enriched emergency notification services. \n In my research, I was amazed to discover how prevalent IoT and Messaging Protocols are across various industries. Here are some examples: \n \n \n \n \n \n Automotive: MQTT can be used by automotive manufacturers to collect car’s sensors data to process them centrally and give more assistance to the driver and enrich the driving experience and security. It is also used to deliver software updates over-the-air or to augment navigation systems capabilities. \n Logistics: MQTT can be used for real-time tracking of assets and transportation vehicles. It is also used to have a constantly up to date inventory of stocks. \n Retail: Smart stores, inventory, customer tracking and analytics, Point-of-Sale integration. \n Manufacturing: Robots and equipment monitoring to identify failures and improve energy consumption, optimize productivity efficiency, coordination between supply chains. \n Medical & Healthcare: With the progress in medical technologies, the cost of medical consultations combined with the lack of medical care in rural areas, there is greater need than ever to provide remote patient monitoring for vital metrics such as blood pressure or blood sugar. Data can be collected by connected medical equipment at home and sent to a central location for analysis and alerting. \n Smart Home: anything that can make you change your Internet router configuration from a /24 to a /16 network like multimedia, light controls, Temperature, home security… \n Smart Cities: Monitoring any environmental factor such as air quality, weather, temperature or react rapidly to emergency situations. \n Oil & Gas: Petrochemical industries are very sensitive and require constant monitoring and control, safety monitoring and alerting and environment observability. \n … \n \n \n 1.4. Alternatives to MQTT \n When it comes to considering a communication protocol for IoT or Machine-2-Machine data exchange, you need to consider the capabilities and constraints of the devices themselves: \n \n Energy efficiency so it does not drain too much power when devices are powered by USB or batteries. \n Performance, depending on the use case the device could receive multiple measurements per minute and needs to respond to consumers sub-second. \n Resource requirements – devices that are affordable and can fit in a constrained space. \n Network quality: In many cases, IoT devices need to communicate over-the-air via mobile networks where network quality is not always guaranteed. \n Message reliability: Unfortunately, packet loss can be a reality. Depending on the use case and the importance of every single message, it should have an inner mechanism to reduce packet loss and retransmit missing packets. \n Queueing: In large-scale deployments, thousands or up to millions of devices will be exchanging messages rapidly. The infrastructure should scale and have a modern message bus that clients can connect to in order to publish or subscribe to messages. \n \n - … \n \n Although there are multiple choices for communication protocols such as: Constrained Application Protocol (CoAP), eXtensible Messaging and Presence Protocol (XMPP), Advanced Message Queuing Protocol (AMQP) and of course Hypertext Transfer Protocol (HTTP), MQTT is, by far, the one that has the best balance between network/hardware/energy requirements vs reliability/queueing/network capabilities. \n Of course, when ample physical space and power supply afford you the ability introduce edge computing capabilities, other protocols like Websockets and gRPC can also be considered. However, you may need to explicitly manage resiliency and message bus distribution capabilities when using these protocols. \n References: \n https://core.ac.uk/download/pdf/160743474.pdf \n \n 2. Architecture \n 2.1. Overall Architecture \n \n \n \n \n 2.2. Terminology \n 2.2.1. Topic \n An MQTT Topic is an identifier or a filter for the message. \n For example, a temperature sensor can send a message with the following topic “temperature/house/floor1/room3”. \n \n 2.2.2. Message \n The message is the payload of the MQTT publication for a specific topic. \n Following the same temperature example, the message can be “20 degrees Celsius” \n \n 2.2.3. Subscriber \n An MQTT subscriber “subscribes” to particular topics available on a MQTT Broker and can read the related messages. \n A subscriber can ask for specific topics “temperature/house/floor1/room3” or wildcard the topics to get all messages under a specific topic level. For example: I can read all MQTT messages related to temperature by subscribing to “temperature/#” \n \n 2.2.4. Publisher \n An MQTT publisher sends messages with a topic to a MQTT Broker. \n \n 2.2.5. Broker \n A broker is a server that receives MQTT messages as input from publishers and in turn publish them to subscribers. \n \n 2.2.6. Who is the Client, who is the Server? \n A client is a device or an application, such as an IoT device or a mobile app, making an MQTT connection to the broker. \n \n Clients and Servers can be either MQTT publishers, subscribers, or both. \n \n 2.3. Traffic overview \n \n \n \n \n \n \n 2.4. MQTT Quality of Service (QoS) \n Unfortunately, the reality is we are delivering messages to and from constrained devices over unreliable networks. When consider a temperature sensor, it may be not so catastrophic to miss a temperature measurement within a 5-minute time slot, but for other use cases like healthcare or automotive, omissions can have tragic consequences. Therefore, we need to consider Quality of Service (QoS) levels that can be associated with MQTT implementations. \n MQTT has 3 levels of QoS: \n - QoS 0 – “at most once” aka fire and forget: the message is sent without confirmation or follow-up \n \n \n \n \n - QoS 1 – “at least once”: the publisher keeps a copy of the published message until it receives a PUBACK confirmation reception message from the broker. If it does not receive a successful receipt message from the broker before expiration of a timeout period, it resends the message. \n \n \n \n \n \n - QoS 2 – “exactly once”: when the publisher sends a message to the broker, it expects a PUBREC acknowledgement. On receiving the PUBREC, the sender removes the packet and sends a PUBREL to tell the broker to release the message If it does not receive any during a timeout period, it sends the PUBLISH packet with a duplicate flag (DUP) \n \n \n \n So, how to select an appropriate QoS value? First, I would say: just put “2” and add to it “which can do more can do less” but I think again at the constrained devices. The higher the QoS level, the more bandwidth and compute it requires. \n Here are few tips on how to choose the best QoS: \n - QoS0 is faster than QoS1 which is faster than QoS2. \n - Use QoS0 if you have a very reliable network. \n - QoS1 tolerates duplicate messages. \n - Use QoS0 when you don’t mind losing some message occasionally. \n \n \n 2.5. Load Balancing of brokers \n Of course, like any networking service, MQTT Brokers should be deployed in N redundant instances to provide capacity and high availability. \n As with any stateful protocol you try to load balance, you need stickiness or persistency to make sure a single MQTT publisher sticks for the same connection to the same broker. \n What happens when you do not have an appropriate session persistence mechanism and you have set up QoS? You cannot rely completely on source IP address as a persistence criterion, as connected devices can roam across networks thus present themselves with a different IP address and be connected to a different broker every time. \n \n 2.5.1. Extend Natively with NGINX \n NGINX can get the client_id from the MQTT packet and persist on it. \n NGINX can substitute the client ID during the MQTT CONNECT message, which most of the time should be a unique identifier such as the serial number of the device combined with a different identifier (such as the client SSL certificate serial number). \n stream {\n mqtt on;\n\n server {\n listen 2883 ssl;\n ssl_certificate /etc/nginx/certs/emqx.pem;\n ssl_certificate_key /etc/nginx/certs/emqx.key;\n ssl_client_certificate /etc/nginx/certs/ca.crt; \n ssl_session_cache shared:SSL:10m;\n ssl_verify_client on;\n proxy_pass 10.0.0.113:1883;\n proxy_connect_timeout 1s; \n\n mqtt_set_connect clientid $ssl_client_serial;\n }\n}\n \n \n 2.5.2. Extend with NJS \n njs is a subset of the JavaScript language that allows extending nginx functionality. The traditional use cases for njs are: \n \n Complex access control and security checks in njs before a request reaches an upstream server \n Manipulating response headers \n Writing flexible asynchronous content handlers and filters \n \n You can find a great example of MQTTv5 implementation extending the capabilities with NJS on Doug_Gallarda personal GitHub repository: https://github.com/gallarda/mqtt5 \n \n 3. MQTT Brokers \n 3.1. Most popular MQTT brokers \n The purpose of this document is not to compare MQTT brokers; simply introduce you to the concept. You can find plenty of comparisons on the Internet. For example, this one https://emqx.medium.com/a-comprehensive-comparison-of-open-source-mqtt-brokers-2023-e70257cc5b75 and https://www.emqx.com/en/blog/open-mqtt-benchmarking-comparison-mqtt-brokers-in-2023 which were both written by EMQ Technologies. I am not making any bias judgement in the ranking, but rest assured you will find the content to be flush with detail. \n Amongst the most popular MQTT brokers we have the following: \n \n Mosquitto \n HiveMQ \n EMQX \n Solace \n \n Depending on the solution you choose, licensing may be set per broker host, per connections and/or messages per second. \n Beyond sharing message processing loads evenly between brokers, an intermediate proxy can block undesirable and unauthenticated connections attempts, filter legitimate and well-structured messages so you pay only for real production traffic. \n \n 3.1. Why proxy MQTT traffic? \n In 2022, the Eclipse Foundation published an IoT & Edge Developer Survey Report which highlighted some concerns related to this. Examine the following chart presented in this report: \n \n The Eclipse foundation explains these numbers by: \n \n An increase in connectivity concerns underscores the lack of computational capacity for efficient built-in security. \n Security still resembles major concern despite the percentage drop (from 46% in 2021) \n A decrease in deployment-related concerns (from 31% to 20% in 2022) indicates that less solutions are moving past the PoC phase, and developers are focusing more on successful solutions rollout to assure overall better user experience. \n Concerns around integration complexity have also decreased (by 11% compared to 2021). As the number of deployments increase, developers see less complexity in the need for additional integrations with complementary technologies and systems. \n \n \n \n 4. MQTT Security \n \n 4.1. Security Context and Attack surface \n In early 2024, did you hear about the 3 million toothbrushes conducting a massive DDoS attack? (https://www.securityweek.com/3-million-toothbrushes-abused-for-ddos-attacks-real-or-not/). As it turns out, this was fake news. However, this scenario is certainly within the realm of possibility. \n In fact, massive DDoS attacks directed by botnets of IoTs is very common. Think about billions of devices (~25B in 2024 according to analysts) with a fair portion of them being completely vulnerable: \n \n Not encrypted \n Never updated \n Poor code \n \n I am not saying it happens because of a lack of security awareness, knowledge or skills, I honestly think it is because of a trade-off engineers made between the technical overhead of security requirements and: \n \n The lightness of the MQTT protocol in terms of hardware requirements for clients. Due to their reduced form factor, their power requirements and price, MQTT devices are generally constrained devices as per RFC 7228 which cannot handle optimal TLS processing. \n The large number of devices makes it difficult to manage the security settings, updates and credentials management over-the-air at scale. \n \n Of course, sometimes there is also a lack of security awareness and the appreciation of the impact of a cyber-attack. \n \n 4.2. IoT devices generally don’t encrypt communication \n This is a bold claim. How do we know this? Leverage one of the first steps employed by ethical hackers: reconnaissance! \n Let’s search for opened non encrypted MQT devices on Internet. How? There are various search engines that discover and index internet-connected devices. Shodan is one of such services. You can run a search on Shodan for: MQTT port: 1883 code:0 and see results like the following: \n \n Notes: \n - 1883 is the default port for unencrypted MQTT. \n - Code:0 indicates unauthenticated \n I was looking into whitepapers on MQTT security, and I found several publications with Shodan outputs April 27 th , 2017 = 24,998 brokers with default ports successfully indexed by Shodan (https://www.researchgate.net/figure/Result-of-MQTT-broker-on-port-1883-in-Shodan_fig2_322059897) and they were just looking for MQTT brokers on port 1883 regardless of their Connection code. \n Now (February 29 th , 2024), and only unauthenticated brokers, I get x19 results. \n Now, second step is looking for authentication, any brokers having a connection code of 0 will accept any clients without any authentication. Again, any client means both publishers AND subscribers. In this case, you can pretty much choose what you want to exploit: \n \n Read for confidential data (you can subscribe to all topics with “#”) \n Drain out messages from brokers (you can ACK messages, so they are deleted from brokers). \n Spam the subscribers by publishing wrong messages. \n Flood with bad messages (i.e. L7 DDoS: search for mqtt malaria on google, there are plenty of open MQTT “stress” tools L). \n \n \n \n 4.3. Authentication and access control \n MQTT brokers supports username password authentication. If no credentials are provided, you will get a connection code of 5, if your credentials are wrong the connection code will be 4. \n Again, if traffic is not encrypted, every part of your MQTT packet is in clear text including username and password. \n Like any username/password authenticated application, brokers are subject to brute force, directory or credential stuffing attacks. \n \n \n 4.4. Injections \n So far, we have discussed the implications of attacks on the publisher, broker and subscriber components. What are some secondary consequences? \n \n A subscriber will likely store the message data somewhere in a database. SQL database? J \n Unfiltered message data may be presented in a modern webpage? J \n MQTT is a TCP messaging protocol that can’t be inspected by traditional L7 security solutions? J \n \n I did a small test with a simple paho python (https://pypi.org/project/paho-mqtt/) MQTT temperature app (reach out if you want the code). \n Note: \n Paho provides a client class which enables applications to connect to an MQTT broker to publish messages, and to subscribe to topics and receive published messages. It also provides some helper functions to make publishing one off messages to an MQTT server very straightforward. \n I was too lazy to set up a SQL database and store data into it. So, I am just sharing the JSON received data from the python code to Flask. So no SQL Injection for today,… XSS will be enough. \n \n \n \n \n And, here what I got on the web app rendering the temperature: \n \n The XSS attack has been successfully made its way until the web application without being identified and intercepted because it have been encapsulated in a MQTT message which cannot be inspected natively by a WAF. \n \n 5. How can NGINX enrich your MQTT use cases? \n 5.1. What is NGINX? \n NGINX is a lightweight and highly performant software-based load balancer and reverse proxy. It natively supports multiple protocols like HTTP for general-purpose web and API traffic but also more specific protocols like MQTT. \n NGINX possesses many built-in features for traffic processing and handling. However, it can also be extended by the usage of its Javascript scripting engine, called NJS (https://nginx.org/en/docs/njs/). NJS can be used to take actions like steering traffic or rewriting packet contents based on multiple conditions. \n \n There are multiple use cases where NGINX, either natively or by extending the capabilities using NJS for parsing and taking decision: \n \n 5.2.Traffic optimisation \n \n Reduce latency \n Uniform load balancing of brokers \n Steering messages to brokers based on topic \n Steering messages to brokers based on QoS \n Steering messages to brokers based on QoS \n Steering messages to brokers based on message content \n ... \n \n \n 5.3.MQTT Security \n \n TLS Offload \n Client Authentication offload \n Client Authorization (filter only to publish not to subscribe for example). \n Filtering broker fingerprinting attempts \n Filtering unwanted information ($SYS) \n Inspecting messages for injection attempts. \n \n \n 5.4. Analytics and Telemetry \n NGINX provides an OpenTelemetry module to help you analyze your software performance by instrumenting, generating, collecting, and exporting telemetry data. \n https://docs.nginx.com/nginx/admin-guide/dynamic-modules/opentelemetry/ \n 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for IoT Devices and Why It’s Important","conversation":{"__ref":"Conversation:conversation:326309"},"id":"message:326309","revisionNum":7,"uid":326309,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:419633"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":184},"postTime":"2024-02-21T13:30:17.504-08:00","lastPublishTime":"2024-03-14T10:15:26.056-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" \n IoT \n We do use Personal Computers (PC) and server/client computers that run Windows, Linux, etc. PCs are used for helping human activity, thus the computer network is basically for displaying/output info/video/audio to humans and input by humans, so it is Human to Human (H2H) network. When we talk about CyberSecurity, that refers to those server/client PCs and TCP/IP security. \n Other than PC,s there are Micro Computers/Embedded Computers that are used for Home Electronics, Factory machines, live cameras, or small devices. Most of them were used to work for in-house tasks and were not connected to the Internet with TCP/IP protocol until recently. \n By the way, I think the iPhone is the most successful computer device that uses the Internet in the history of computers. However, the iPhone (and iPod touch) is not the first handheld device of Apple. Apple released the “Newton” in 1993 which can perform a variety of tasks like the iPhone. However, the sale of the Newton was not good and the project was canceled. \n We are not concerned here with the question of Newton's failure, however, what the iPhone has and what Newton hasn't - is the ability to connect to the Internet. \n As a result of the mass production of iPhone and other smartphones, microcomputers, GPS receivers, and small sensor devices became inexpensive and mass-produced, and Internet connectivity became possible with inexpensive components. \n Naturally, Micro Computers/Embedded Computers are combined with cheap network access devices - the combination of these microcomputers and networks is called Internet of the Things (IoT). \n In most cases, IoT devices relay data from sensors which is attached to the IoT devices, and it relays to other IoT devices to aggregate the data for processing – the IoT devices are connected, and the communications are done among IoT (machines): so it is Machine to Machine (M2M) network. So the IoT devices are also to be M2M network devices. \n One of the well-known examples of IoT devices is the Arduino board which is an open-source electronics platform based on easy-to-use hardware and software. Arduino is easy to program, and deploy, and can use many types of sensors, and the cost is quite low, thus it has been used in thousands (or more) of projects and applications. \n As IoT devices are much cheaper and easier to produce compared to the PC, the number of IoT devices increases rapidly, and no limitation on the producing number. In contrast, the demand for PCs (and smartphones) is limited by the number of humans. \n The number of IoT devices that are connected (cite from statista) \n \n \n \n \n 2019 \n 8.6 billion \n \n \n 2023 \n 15.14 billion \n \n \n \n \n As the number of IoT devices increases, the network connecting IoT devices (M2M) increases geometrically. \n By the way, BigIP LTM has a profile to use one of the protocols which is used for IoT networks ( Local Traffic ›› Profiles : Services : MQTT ). \n \n Security Concerns \n What problems will arise from IoTs? \n Attack surface \n First, unlike servers and PCs, these IoT devices are small and can be transported anywhere (laptop PC is portable, but limited to the space where human goes). A good example is drones – which has microcomputers and network connecting devices thus IoT - that can move autonomously from place to place, even to the place humans can’t go. Therefore, they are not restricted access by physical location and can be connected to the Internet wherever they are located. Therefore, unlike servers and PCs, it is difficult to know the location of all IoT devices in the world. The problem is that IoT devices are directly accessible by malicious attackers: they can be everywhere and the number of devices are too many to track all of them. \n From the network perspective, servers and PCs are always protected because they have limited physical access points = Attack Surface, and even if they become the source of an attack, the locations of the malicious attacker’s host can be determined to some extent. The CVSS metrics score low when the PC/Servers are not accessible via the network. \n \n In contrast, since it is hard to know all the locations of IoT devices and their M2M network connection points, the Attack Surface is everywhere. If an IoT device that is located in an unknown (physical) place is compromised and becomes a jump host, it might be difficult for a defender to know where the attack is coming from. In other words, being everywhere because it is convenient also means not knowing where they are. We need to think about expanding the attack surface. \n You may recall the Mirai botnet - Mirai's primarily targets IoT devices such as IP cameras and home routers - IP cameras can be placed on the outside of the building so easy to access for the malicious attacker. \n In the Keynote speech of BlackHatAsia 2019, the presenter of the speech said that “IoT is next asbestos!” \n Not only physical access, the range of the network is going to be expanding. As the number of network devices increases, the amount of network connecting them also increases geometrically, so the network that needs to be monitored will also expand. \n Network protocol \n Second, many IoT devices use protocols other than TCP/IP. Since they were used in the closed network before the IoT era like in the factory or car, the design and implementation of such protocols do not need to consider security and privacy. However, once it connects to the Internet, attacks against them are often easy due to the nature of those protocols, which are not security-conscious, and the lack of research that has been done on them may make these attacks possible. \n For example, the CAN network is used for in-vehicle (i.e. car) networks, which have no destination or source address. Therefore, it is difficult to identify and block the source of an attack through the CAN network. \n Some IoT devices communicate through TCP/IP and HTTP protocol, but not HTTPS – it is because those devices are designed to be using small memory and narrow network bandwidth. Of course, it is not secure. \n The amplified DDOS attack \n As mentioned above, the number of the PC is limited while the IoT devices are limitless. And the protocol has some security weaknesses – so the IoT devices could be compromised and used as jump hosts for DDOS campaigns. The jump hosts which is used for the DDOS attack will be amplified - more than that of the H2H network, and it make it difficult to defend. \n Mirai botnet is one of the most famous IoT attacking bots. Quote from What was the Mirai botnet? \"In late 2016 in France, telecom company OVH was hit by a distributed denial-of-service (DDoS) attack. Experts were struck by how the assault was 100 times larger than similar threats.\" This incident happened in 2016 - as shown above, we have more and more IoT devices. \n \n Defense \n IoT devices behave differently than PC/Servers and require their own cybersecurity rules depending on how they operate. To reduce the risks of IoT devices, some system standards and security guidelines for IoT have been published by governments and non-profit organizations. \n USA IoT Cyber Security Improvement Act of 2020 https://www.govinfo.gov/content/pkg/COMPS-15863/pdf/COMPS-15863.pdf \n NIST IoT Device Cybersecurity Guidance for the Federal Government \n https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-213.pdf \n USA DHS : Strategic Principles for Securing the Internet of Things https://www.dhs.gov/securingtheIoT \n IEEE IoT security best practices white paper \n https://standards.ieee.org/wp-content/uploads/import/documents/other/whitepaper-internet-of-things-2017-dh-v1.pdf \n To mitigate the risk, IoT devices need to consider implementing security measures when it is designed. For example, access control feature and user(machine) authorization to change the config, implement encryption (while it is a performance trade-off), monitor the abnormality, and use Edge computer to filter the data and proxy the connection. \n And, of course, not using default user/Password is essential – the Mirai botnet will use them. \n In most cases the data from IoT devices will be uploaded to cloud service and processed on the application layer – thus application firewall can be one of the protection measures. \n \n Future \n Think about the future – the number of IoT devices, the M2M network, and the amount of data on the M2M network will be exponentially increased, thus humans might be overwhelmed to monitor and analyze the network. Recently generative AI has been used for large amounts of data, so AI will also be used for IoT security. As discussed in another article, the security of AI is also important, and, if AI and IoT are united, things need to be considered might be more. \n \n Further study \n Thesis of IoT security in arxiv: \n A Survey of the Security Challenges and Requirements for IoT Operating Systems https://arxiv.org/abs/2310.19825 \n A Unified Taxonomy and Evaluation of IoT Security Guidelines https://arxiv.org/abs/2310.01653 \n Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future https://arxiv.org/abs/2309.02707 \n A Large-Scale Study of IoT Security Weaknesses and Vulnerabilities in the Wild https://arxiv.org/abs/2308.13141 \n Unleashing IoT Security: Assessing the Effectiveness of Best Practices in Protecting Against Threats https://arxiv.org/abs/2308.12072 \n IoT and Man-in-the-Middle Attacks https://arxiv.org/abs/2308.02479 \n 5G Networks and IoT Devices: Mitigating DDoS Attacks with Deep Learning Techniques https://arxiv.org/abs/2311.06938 \n IoT in the Era of Generative AI: Vision and Challenges https://arxiv.org/abs/2401.01923 \n 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Internet of Sports","conversation":{"__ref":"Conversation:conversation:280604"},"id":"message:280604","revisionNum":1,"uid":280604,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:321706"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":442},"postTime":"2014-08-13T05:20:00.000-07:00","lastPublishTime":"2014-08-13T05:20:00.000-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Did you see what the NFL is doing this year with sensors? \n\n Earlier this month they announced a partnership with Zebra Technologies, a company that provides RFID chips for applications from 'automotive assembly lines to dairy cows' milk production.' This season there will be sensors in the player's shoulder pads which will track all their on field movements. This includes player acceleration rates, top speed, length of runs, and even the distance between a ball carrier and a defender. Next year they'll add sensors for breathing, temperature and heart rate. More stats than ever and could change the game for-ever. Imagine coaches being able to examine that data and instantly call a play based on it. Play by play. To me it somewhat takes away that 'feel' for the game flow but also having data to confirm or deny that feeling might make for exciting games. Maybe lots of 0-0 overtimes or a 70-0 blowout. Data vs. data. Oh how do I miss my old buzzing electric football game. \n\n The yardsticks will have chips along with the refs and all that data is picked up by 20 RFID receivers placed throughout the stadium. Those, in turn, are wired to a hub and server which processes the data. 25 times a second, data will be transmitted to the receivers and the quarter sized sensors use a typical watch battery. The data goes to the NFL 'cloud' and available in seconds. The only thing without a sensor is the ball. But that's probably coming soon since we already have the 94Fifty sensor basketball. \n\n And we've had the NASCAR RACEf/x for years and this year they are going to track every turn of the wrench with RFID tracking in the pits and sensors on the crew. Riddell has impact sensors in their helmets to analyze, transmit and alert if an impact exceeds a predetermined threshold. They can measure the force of a NBA dunk; they can recognize the pitcher’s grip and figure out the pitch; then the bat sensor that can measure impact to the ball, the barrel angle of their swings, and how fast their hands are moving; and they are tracking soccer player movement in Germany. Heck, many ordinary people wear sensor infused bracelets to track their activity. \n\n We've come a long way since John Madden sketched over a telestrator years ago and with 300 plus lb. players running around with sensors, this is truly Big Data. It also confirms my notion that the IoT should really be the Internet of Nouns - the players, the stadiums and the yardsticks. \n\n ps \n\n Related: \n\n Player-tracking system will let NFL fans go deeper than ever Fantasy footballers and coaches rejoice—NFL players to wear RFID tags More sensors are coming to professional sports, but research outpaces business models Why This Nascar Team Is Putting RFID Sensors On Every Person In The Pit Impact Sensors: Riddell InSite Impact Response System Fastpitch Softball League Adds Swing Sensors to its Gear \n\n \n\n Technorati Tags: rfid,sensors,IoT,things,nfl,cloud,big data,silva,f5 \n\n \n\n Connect with Peter: Connect with F5: ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"3102","kudosSumWeight":0,"repliesCount":1,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODA2MDQtNDkyMWk3OTMyNzdCMDg5MDhBRDIx?revision=1\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODA2MDQtMzUyN2k1OUExNUNEM0ZEOUQ0QzZB?revision=1\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDM","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODA2MDQtODU2MGk2QkNEN0U4RDIzMTRDODIx?revision=1\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDQ","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODA2MDQtMTE3MzJpM0E4OEVGQkREODAwOEVEMw?revision=1\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDU","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODA2MDQtNzg5aTE0NUM2OUY4MUY3MUFFQjM?revision=1\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDY","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODA2MDQtMzQ3NWk3Qjg2OTYyMzNERDMzOURC?revision=1\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDc","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODA2MDQtNTk4M2k1MzIwOUY5NEIzNUM0RUQ5?revision=1\"}"}}],"totalCount":7,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:285373":{"__typename":"Conversation","id":"conversation:285373","topic":{"__typename":"TkbTopicMessage","uid":285373},"lastPostingActivityTime":"2019-09-17T04:35:06.000-07:00","solved":false},"User:user:332812":{"__typename":"User","uid":332812,"login":"Payal_S","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://community.f5.com/t5/s/zihoc95639/m_assets/avatars/default/avatar-11.svg?time=0"},"id":"user:332812"},"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODUzNzMtMjc5MGkxQkQ3MjA5OTk2RTExRTVB?revision=1\"}":{"__typename":"AssociatedImage","url":"https://community.f5.com/t5/s/zihoc95639/images/bS0yODUzNzMtMjc5MGkxQkQ3MjA5OTk2RTExRTVB?revision=1","title":"0151T000003d70xQAA.png","associationType":"BODY","width":992,"height":422,"altText":null},"TkbTopicMessage:message:285373":{"__typename":"TkbTopicMessage","subject":"F5 BIG-IP MQTT protocol support and use cases in an IoT environment","conversation":{"__ref":"Conversation:conversation:285373"},"id":"message:285373","revisionNum":1,"uid":285373,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:332812"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":3420},"postTime":"2017-05-09T09:00:00.000-07:00","lastPublishTime":"2017-05-09T09:00:00.000-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" The Internet-of-Things is a system of physical devices, vehicles, buildings, and any other items each provided with a unique identifier allowing them to communicate with one another without any human intervention. MQTT is a widely-used machine-to-machine connectivity protocol that helps these devices communicate and exchange messages. The wide adoption and popularity of the MQTT protocol led to its support in the BIG-IP version 13.0. \n\n MQTT is a publish/subscribe messaging protocol. A device such as a camera, heat sensor, lP-enabled light bulb, etc. can publish data to an intermediary module using the MQTT protocol. An application can then subscribe to this intermediary module and retrieve the published data. Intermediary modules are also known as message brokers. The BIG-IP with MQTT awareness can sit in front of the MQTT message brokers to provide scalability, security, visibility, and availability. \n\n \n\n Fig. 1 – Basic architecture of using the BIG-IP platform in an IoT environment. \n\n In an MQTT configuration, clients publish messages and the BIG-IP system parses those MQTT messages based on which it invokes MQTT specific iRule events if defined and performs connection based load balancing on the MQTT messages to a pool of message brokers. The message brokers then transport and route the messages to subscribing servers \n\n A typical BIG-IP MQTT configuration includes: \n\n MQTT pool of message brokers\n Are grouped together to receive and process traffic. After the pool is created, associate the pool with a virtual server. Some common open source message brokers examples are Mosquitto and VerneMQ \n iRules for MQTT\n Use iRules to exercise MQTT functionality, for example to log the messages that the BIG-IP system passes, or to pass the client certificate's common name in the CONNECT message \n Client SSL profile\n Use a Client SSL profile when you want the BIG-IP ® system to authenticate and decrypt/encrypt client-side application traffic \n Virtual server configured to use MQTT functionality \n\n For more details please refer to: https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/ltm-iot-administration-13-0-0/1.html \n\n BIG-IP natively supports the MQTT protocol. BIG-IP has a full proxy architecture which makes BIG-IP itself an endpoint and an originator of the MQTT protocol. iRules take advantage of the deep understanding of the protocol and can be used at different events (specific moments within the session flow of a network connection, such as MQTT_CLIENT_INGRESS, MQTT_SERVER_INGRESS) to intelligently parse the MQTT protocol and make traffic decisions. \n\n Let’s explore some of the use cases using iRules such as load balancing and steering traffic based on a unique identified present within the MQTT protocol, preventing attacks based on TOPICS/LENGTH of a PUBLISH message, client authentication based on CN name present in the client certificate. \n\n Use Case: prevent MQTT DDoS attacks based on the below parameters \n\n Topic validation \n\n Validate the ‘TOPIC’ of a PUBLISH message and if it does not fit the validation criteria then drop the connection. This will prevent messages with bogus TOPICS from reaching the message brokers. And help in preventing MQTT DDoS attacks based on TOPIC. \n\n \nwhen MQTT_CLIENT_INGRESS {\nlog local0. \"CLIENT [MQTT::type]\"\n if {[MQTT::type] eq \"PUBLISH\" } {\n # Check against a allowed topic.\n if { [MQTT::topic] eq \"bogus/bogus\" } {\n # Invalid topic\n log local0. \" Topic is Invalid. Potential DDoS Attack -> Dropping Topic: [MQTT::topic]\"\n drop\n }\n } \n} \n\n The above iRule can be enhanced to use data groups where the data groups will have the entire list of TOPICS and the [MQTT::TOPIC] can be checked against the data group \n\n MQTT PUBLISH message length validation \n\n An application will typically have knowledge about the size of the data that is being transmitted. Taking advantage of that knowledge the length of a PUBLISH message can be validated and if it does not satisfy the expected length then drop the connection. This will prevent large messages from reaching the message brokers and not overload the broker. \n\n \nwhen MQTT_CLIENT_INGRESS {\nlog local0. \"CLIENT [MQTT::type]\"\n if {[MQTT::type] eq \"PUBLISH\" } {\n # Check length of message.\n if { [MQTT::length] > 100 } {\n # Invalid length\n log local0. \" Length is Invalid. Potential DDoS Attack -> Dropping message: [MQTT::topic] : [MQTT::length]\"\n drop\n }\n } \n} \n\n Use Case: pool selection/load balancing based on username as a unique identifier \n\n Use the username as a unique identifier to steer traffic to a message broker. This enables stickiness between an end user and a message broker by mapping a device/end user to a pool in the load balancer. The mapping helps in conditions where in a device needs to reconnect to the message broker on which the active client session lives and can use the state information present on the message broker to make decisions. \n\n \nwhen MQTT_CLIENT_INGRESS {\nlog local0. \"CLIENT [MQTT::type]\"\n if {[MQTT::type] eq \"CONNECT\" } {\n # Select pool based on username, example license ID\n if { [MQTT::username] eq \"D1111111\" } {\n log local0. \"Load balancing to pool MQTT-BrokerPool1\"\n pool MQTT-BrokerPool1\n }\n if { [MQTT::username] eq \"D1111112\" } {\n log local0. \"Load balancing to pool MQTT-BrokerPool2\"\n pool MQTT-BrokerPool2\n }\n } \n} \n\n The above iRule can be enhanced to use data groups where the data groups will have the list of unique usernames. Multiple data groups can be defined, each one representing users for multiple Pools. The [MQTT::username] can be checked against the data group and based on that the pool selection can be made. \n\n Use Case: client certificate authentication over TLS \n\n BIG-IP can terminate MQTT encrypted SSL/TLS messages and then send the un-encrypted traffic to the backend Broker. This allows the Broker to scale as it can offload all SSL/TLS functions and configuration to the BIG-IP. In addition to terminating SSL/TLS the BIG-IP can use iRules to perform Client Certificate Authentication. The BIG-IP can embed the client CN name from the client certificate into the backend connection along with the username for authentication by the back-end Broker. \n\n \nwhen CLIENT_ACCEPTED {\n set cn \"\"\n}\n\nwhen CLIENTSSL_CLIENTCERT {\n log local0. \" Parsing X509 Info for SSL Client Cert CN Name\"\n set cn [findstr [X509::subject [SSL::cert 0]] \"CN=\" 3 \",\"]\n log local0. \"Found Client Cert Common Name (CN) : $cn\"\n}\n\nwhen MQTT_CLIENT_INGRESS {\n log local0. \"MQTT Client MmessageTtype [MQTT::type]\"\n if {[MQTT::type] == \"CONNECT\"} {\n log local0. \"Connecting to Broker\"\n if {$cn == \"\"} {\n # if we didn't see a client cert, return an authentication error \n MQTT::drop \n MQTT::respond type CONNACK return_code 5\n MQTT::disconnect \n } else {\n log local0. \"Passing Username and CN to Backend for Authentication\"\n log local0. \"MQTT Username: [MQTT::username]\"\n log local0. \"Username: [MQTT::username] CN: $cn\"\n set mqttuser [MQTT::username]\n MQTT::username \"$mqttuser $cn\" \n }\n }\n } \n\n Conclusion \n\n Bookmark this page if you are interested in learning more. We will be update this blog with new compelling IoT features developed by F5 for the upcoming BIG-IP releases. \n\n Do you have a suggestion for an IoT related topic that you would like for us to cover? Please leave a comment on this post if you do. \n\n References \n\n https://support.f5.com/kb/en-us/products/big-ip_ltm/manuals/product/ltm-iot-administration-13-0-0/1.print.html https://devcentral.f5.com/s/articles/lightboard-lessons-iot-on-big-ip-24923?tag=lbl https://devcentral.f5.com/s/articles/the-iot-ready-platform https://f5.com/resources/white-papers/tmos-redefining-the-solution https://devcentral.f5.com/s/articles/the101-irules-101-events-amp-priorities https://en.wikipedia.org/wiki/MQTT https://mosquitto.org/ ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"8268","kudosSumWeight":0,"repliesCount":1,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODUzNzMtMjc5MGkxQkQ3MjA5OTk2RTExRTVB?revision=1\"}"}}],"totalCount":1,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:281664":{"__typename":"Conversation","id":"conversation:281664","topic":{"__typename":"TkbTopicMessage","uid":281664},"lastPostingActivityTime":"2018-09-19T19:53:00.000-07:00","solved":false},"User:user:56738":{"__typename":"User","uid":56738,"login":"ltwagnon","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://community.f5.com/t5/s/zihoc95639/images/dS01NjczOC0xNjM3OGk3QkQ0M0UxRDAzRDEzMDg3"},"id":"user:56738"},"TkbTopicMessage:message:281664":{"__typename":"TkbTopicMessage","subject":"Lightboard Lessons: Exploiting Cellular IoT Gateways","conversation":{"__ref":"Conversation:conversation:281664"},"id":"message:281664","revisionNum":1,"uid":281664,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:56738"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":274},"postTime":"2018-09-19T19:53:00.000-07:00","lastPublishTime":"2018-09-19T19:53:00.000-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Critical emergency services such as police, fire, and medical manage their fleets with vulnerable cellular IoT devices. “Vulnerable” doesn’t have to mean a vulnerability within the hardware or software, although we suspect that is the case in some makes and models. In this instance, \"vulnerable\" can mean being susceptible to remote attacks because of weak access control and use of default credentials. An attacker can use these vulnerable device to launch attacks, as we have seen with thingbots like Mirai and Reaper, or they can use that access for nefarious purposes to spy, redirect commands in the case of a fleet taking orders from a remote command, or shut the system off, effectively disabling operations. In this video, John outlines the problem of weak authentication in widely-used cellular gateway devices. Help spread the word, and for the love of all things security, change your default usernames and passwords! \n\n \n\n \n\n Related Resources: \n\n F5 Labs Report: Breaking Down the Door to Emergency Services through Cellular IoT Gateways F5 Labs Report: Leveraging Government Transparency to Find Vulnerable Cellular Gateways ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"1194","kudosSumWeight":0,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:280828":{"__typename":"Conversation","id":"conversation:280828","topic":{"__typename":"TkbTopicMessage","uid":280828},"lastPostingActivityTime":"2017-10-20T06:53:06.000-07:00","solved":false},"TkbTopicMessage:message:280828":{"__typename":"TkbTopicMessage","subject":"Post of the Week: Explaining the KRACK Vulnerability","conversation":{"__ref":"Conversation:conversation:280828"},"id":"message:280828","revisionNum":1,"uid":280828,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:56738"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":352},"postTime":"2017-10-19T12:27:00.000-07:00","lastPublishTime":"2017-10-19T12:27:00.000-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" In this \"Post of the Week\" video, we discuss the KRACK vulnerability that targets mobile devices and wireless routers. This vulnerability targets the WPA2 security protocol that allows for encryption between a mobile device and a wireless router. As the mobile device negotiates encrypted communication with the router, an attacker can force the mobile device to use very weak encryption (essentially no encryption at all) and thus see all the traffic between the device and the router. We also talk about ways you can help avoid this problem. Enjoy! Related Resources \n\n New Threat May Slip Through the KRACK in BYOD Policies (F5 Labs) Scary Candy Week: KRACK and ROCA ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"720","kudosSumWeight":0,"repliesCount":1,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:282967":{"__typename":"Conversation","id":"conversation:282967","topic":{"__typename":"TkbTopicMessage","uid":282967},"lastPostingActivityTime":"2017-10-04T05:00:00.000-07:00","solved":false},"TkbTopicMessage:message:282967":{"__typename":"TkbTopicMessage","subject":"Lightboard Lessons: Connecting Cars with BIG-IP","conversation":{"__ref":"Conversation:conversation:282967"},"id":"message:282967","revisionNum":1,"uid":282967,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:321706"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":470},"postTime":"2017-10-04T05:00:00.000-07:00","lastPublishTime":"2017-10-04T05:00:00.000-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" I light up how BIG-IP and Solace work together in a MQTT connected car infrastructure. \n\n \n\n ps \n\n Related: \n\n Using F5 BIG-IP and Solace Open Data Movement technology for MQTT message routing and delivery Lightboard Lessons: What is MQTT? Solace and F5: Partnering for Better IoT ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"289","kudosSumWeight":0,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:285406":{"__typename":"Conversation","id":"conversation:285406","topic":{"__typename":"TkbTopicMessage","uid":285406},"lastPostingActivityTime":"2017-10-03T04:00:00.000-07:00","solved":false},"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODU0MDYtNzkyNGkyMkIwQzlCNTIxOTBDOUI1?revision=1\"}":{"__typename":"AssociatedImage","url":"https://community.f5.com/t5/s/zihoc95639/images/bS0yODU0MDYtNzkyNGkyMkIwQzlCNTIxOTBDOUI1?revision=1","title":"0151T000003d74jQAA.png","associationType":"BODY","width":760,"height":606,"altText":null},"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODU0MDYtMjUxOGkwN0NGMzFDQjUxRDMzN0NB?revision=1\"}":{"__typename":"AssociatedImage","url":"https://community.f5.com/t5/s/zihoc95639/images/bS0yODU0MDYtMjUxOGkwN0NGMzFDQjUxRDMzN0NB?revision=1","title":"0151T000003d74kQAA.png","associationType":"BODY","width":1302,"height":644,"altText":null},"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODU0MDYtOTE5NGlDMTczN0VFNjE4NjA1Njg4?revision=1\"}":{"__typename":"AssociatedImage","url":"https://community.f5.com/t5/s/zihoc95639/images/bS0yODU0MDYtOTE5NGlDMTczN0VFNjE4NjA1Njg4?revision=1","title":"0151T000003d74lQAA.png","associationType":"BODY","width":1040,"height":133,"altText":null},"TkbTopicMessage:message:285406":{"__typename":"TkbTopicMessage","subject":"Using F5 BIG-IP and Solace Open Data Movement technology for MQTT message routing and delivery","conversation":{"__ref":"Conversation:conversation:285406"},"id":"message:285406","revisionNum":1,"uid":285406,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:332812"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":683},"postTime":"2017-10-03T04:00:00.000-07:00","lastPublishTime":"2017-10-03T04:00:00.000-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" The \"Internet of Things\" (IoT) has the potential to not just impact the way we live and work, but to disrupt entire industries. Some of the major industries that are driving innovation in IoT include manufacturing, transportation, and utilities. In this post I’ll talk about an example of how digital manufacturing is helping automobiles be more intelligent. \n\n There are millions of connected automobiles that have software running on them: from programs that keep GPS maps up to date to sensors sending vehicle speeds or temperature information. This information typically is being sent to a centralized management system that enables intelligent decisions, and those back-end systems also need to send data, instructions, and updates to the cars. \n\n We are actively working with a leading multinational automotive company. In this deployment the management system uses MQTT to send notifications to cars that a new software update is available for download. It is critical that these messages are received by the connected cars, but message delivery can be delayed if the car can’t be reached because it’s out of range, or driving through a tunnel, or even if cellular networks are congested. \n\n Using the Solace message broker \n\n To ensure eventual delivery in such situations, you can have the management system send messages to a message broker that in turn distributes them to intended recipients. This decouples your architecture so the many elements of the management system don’t need to worry about the specific destinations to which each message must be delivered, nor track delivery status. They simply send a message to the broker which A) takes care of routing it to requisite destinations, and B) stores a copy of it until every vehicle that needs it has confirmed receipt. \n\n Basic IIoT architecture for connected automobiles \n\n Before diving deeper, let’s look at the architecture that is used in the above use case. The idea is the same, but to support the numbers of connected vehicles and volume of data involved, it’s necessary to implement multiple message brokers. This architecture is provided by Solace which uses a novel architecture that enables efficient publish/subscribe distribution of data and can scale to millions of connected devices. (see Fig 1.). \n\n Back-end applications connect to a single broker (core message broker) to send a message to any vehicle, and can use messaging techniques preferred by IT applications such as JMS, AMQP and Node.js. The core message broker is communicating to several edge message brokers through internal messaging. The data for a particular vehicle is routed through one edge message broker and delivered to the vehicle in the matter conducive for it, in this case MQTT. \n\n In the diagram, Vehicle 1 connects to Message Broker 1. That means that messages sent from the management system to the core message broker that are intended for Vehicle 1 only need to go to Message Broker 1 \n\n \n\n Fig. 1 – Basic IIoT architecture for connected automobiles \n\n This two-tier approach provides a simple and powerful scaling architecture for north-south communication, since more connected cars can be added by adding more edge message routers without affecting the existing system. \n\n BIG-IP and persistence \n\n For this architecture, we’re aiming to achieve two things: \n\n First, we want to relieve the management system of the burden of keeping track of message delivery to potentially millions of vehicles. The Solace message broker uses MQTT QoS Level 1 which guarantees that a message will be delivered at least once to the receiver. The message is persisted in the edge message broker which allows the backend IoT application to publish messages with confidence that they will eventually reach their destination, but without needing to keep track of message delivery status. \n\n Second, we need to make sure that the vehicle connects to the right message broker so it can receive its messages. This can be achieved by managing a 1:1 mapping between the edge message broker and the vehicle. \n\n \n\n Fig. 2 – F5 BIG-IP in the IoT architecture \n\n BIG-IP version 13+ helps to achieve the 1:1 mapping with support for MQTT message parsing. It sits in front of the message broker and parses the MQTT messages – using iRules – exchanged between the vehicle to the message broker. Data groups on the BIG-IP are used to map a vehicle using a unique Identifier to a pool of message brokers. Using iRules every MQTT message is parsed, then the data group lookup routes the data to the correct pool of message brokers. This helps to achieve a “sticky” load balancing solution so that when a vehicle comes back online it will always get routed and connected to the correct message brokers where the connection state for that vehicle is known to be maintained. We say a “pool of message brokers” in order for the brokers to provide a highly-available service. \n\n Here is some sample code of an iRule that helps with achieving persistence or sticky load balancing: \n\n \n \n \nwhen MQTT_CLIENT_INGRESS {\nlog local0. \"CLIENT [MQTT::type]\"\n if {[MQTT::type] eq \"CONNECT\" } {\n # Select pool based on vehicle ID\n if { [MQTT::username] eq \"D1111111\" } {\n log local0. \"Load balancing to pool MQTT-BrokerPool1\"\n pool MQTT-BrokerPool1\n }\n if { [MQTT::username] eq \"D1111112\" } {\n log local0. \"Load balancing to pool MQTT-BrokerPool2\"\n pool MQTT-BrokerPool2\n }\n } \n} \n \n\n Conclusion \n \n\n IoT use cases which benefit from having a guaranteed delivery of messages can take advantage of F5’s persistence capabilities. The architecture described above means that specific edge broker instances will maintain 'state' for specific connected vehicles. This requires the MQTT load-balancing to be sticky across sessions. BIG-IP version 13+ supports MQTT message parsing using iRules and thereby provides a key functionality in achieving the end-to-end goal of the solution for this type of architecture. \n\n The industries that are embracing “Internet of Things” applications are still in the early stages of innovation, but market leaders are architecting now for scale and resilience so they can automate more and more processes with a single infrastructure. The automaker in this example has chosen F5’s BIG-IP solution for 1:1 mapping of cars to message brokers, and Solace’s Open Data Movement technology as the MQTT infrastructure for message routing and delivery. The combination provides an elegant solution that can scale to millions of connections to support an increasing number of message exchanges between the vehicles and back end systems as their telematics and in-car services get more sophisticated. ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"6765","kudosSumWeight":0,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODU0MDYtNzkyNGkyMkIwQzlCNTIxOTBDOUI1?revision=1\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODU0MDYtMjUxOGkwN0NGMzFDQjUxRDMzN0NB?revision=1\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDM","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODU0MDYtOTE5NGlDMTczN0VFNjE4NjA1Njg4?revision=1\"}"}}],"totalCount":3,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:282615":{"__typename":"Conversation","id":"conversation:282615","topic":{"__typename":"TkbTopicMessage","uid":282615},"lastPostingActivityTime":"2017-02-20T05:00:00.000-08:00","solved":false},"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODI2MTUtMTE3MTdpQzFGRjA2RjU0MUUxQjRGQg?revision=1\"}":{"__typename":"AssociatedImage","url":"https://community.f5.com/t5/s/zihoc95639/images/bS0yODI2MTUtMTE3MTdpQzFGRjA2RjU0MUUxQjRGQg?revision=1","title":"0151T000003d6xsQAA.jpg","associationType":"BODY","width":187,"height":183,"altText":null},"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODI2MTUtMTMyMDBpNEQxN0E1NThENzhFRjJENQ?revision=1\"}":{"__typename":"AssociatedImage","url":"https://community.f5.com/t5/s/zihoc95639/images/bS0yODI2MTUtMTMyMDBpNEQxN0E1NThENzhFRjJENQ?revision=1","title":"0151T000003d6xtQAA.jpg","associationType":"BODY","width":283,"height":190,"altText":null},"TkbTopicMessage:message:282615":{"__typename":"TkbTopicMessage","subject":"What to Expect in 2017: Mobile Device Security","conversation":{"__ref":"Conversation:conversation:282615"},"id":"message:282615","revisionNum":1,"uid":282615,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:321706"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":352},"postTime":"2017-02-20T05:00:00.000-08:00","lastPublishTime":"2017-02-20T05:00:00.000-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" We are mobile, our devices are mobile, the networks we connect to are mobile and the applications we access are mobile. Mobility, in all its iterations, is a huge enabler and concern for enterprises and it'll only get worse as we start wearing our connected clothing to the office. \n\n If the last 10 years wasn’t warning enough, 2017 will be a huge year for mobile…again. Every year, it seems, new security opportunities, challenges and questions surround the mobile landscape. And now it encompasses more than just the device that causes phantom vibration syndrome, it now involves the dizzying array of sensors, devices and automatons in our households, offices and municipalities. Mobile has infiltrated our society and our bodies along with it. \n\n So the security stakes are high. \n\n The more we become one with our mobile devices, the more they become targets. It holds our most precious secrets which can be very valuable. We need to use care when operating such a device since, in many ways, our lives depend on it. And with the increased automation, digitization and data gathering, there are always security concerns. \n\n So how do we stay safe? \n\n The consumerization of IT technologies has made us all administrators of our personal infrastructure of connected devices. Our digital self has become a life of its own. As individuals we need to stay vigilant about clicking suspicious links, updating software, changing passwords, backing up data, watching financial accounts, having AV/FW and generally locking down devices like we do the doors to our home. Even then, the smartphone enabled deadbolt can be a risk. And we haven’t even touched on mobile payment systems, IoT botnets or the untested, insecure apps on the mobile phone itself. \n\n Cybersecurity is a social issue that impacts us all and we all need to be accountable. \n\n For enterprises, mobile devices carry an increased risk, especially personal devices connecting to an internal network. From regulatory compliance to the disgruntled employee, keeping sensitive information secret is top concern. BYOD policies and MDM solutions help as does segmenting those devices away from critical info. And the issue isn’t so much seeing restricted information, especially if your job requires it, it is more about unauthorized access if the device is compromised or lost. Many organizations have policies in place to combat this, including a total device wipe…which may also blast your personal keepsakes. The endpoint security market is maturing but won’t fill the ever-present security gaps. \n\n From your workforce to your customers, your mobile web applications are also a target. The Anti-Phishing Working Group (APWG) reports a 250 percent jump in the number of detected phishing websites between October 2015 and March 2016. Around 230,000 unique phishing campaigns a month, many aimed at mobile devices arriving as worrisome text messages. Late 2016 saw mobile browsing overtake desktop for the first time and Google now favors mobile-friendly websites for its mobile search results. A double compatibility and SEO whammy. \n\n And those two might not be the biggest risk to an organization since weakest link in the security ecosystem might be third-party vendors and suppliers. \n\n On the industrial side, tractors, weather sensors, street lights, HVAC systems, your car and other critical infrastructure are now mobile devices with their own unique security implications. The Industrial Internet of Things (IIoT) focuses on industrial control systems, device to network access and all the other connective sensor capabilities. These attacks are less frequent, at least today, but the consequences can be huge – taking out industrial plants, buildings, farms, and even entire cities. \n\n The Digital Dress Code has emerged and with 5G on the way, mobile device security takes on a whole new meaning. \n\n ps \n\n Related: \n\n Mobile Trends For 2017 And Beyond Perspectives on Securing Mobile and Social Business, 12 Months On RSAC17: More ransomware and IoT-enabled attacks on the way, warns expert Mobile Malware Milestone Mobile banking and how to stay secure What Does Mobile Mean, Anyway? BYOD - concentrate on the apps, not the devices 10 Security Trends To Watch For At RSA 2017 ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"4269","kudosSumWeight":0,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODI2MTUtMTE3MTdpQzFGRjA2RjU0MUUxQjRGQg?revision=1\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://community.f5.com/t5/s/zihoc95639/images/bS0yODI2MTUtMTMyMDBpNEQxN0E1NThENzhFRjJENQ?revision=1\"}"}}],"totalCount":2,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"Conversation:conversation:282727":{"__typename":"Conversation","id":"conversation:282727","topic":{"__typename":"TkbTopicMessage","uid":282727},"lastPostingActivityTime":"2017-02-08T10:00:00.000-08:00","solved":false},"TkbTopicMessage:message:282727":{"__typename":"TkbTopicMessage","subject":"Lightboard Lessons: IoT on BIG-IP","conversation":{"__ref":"Conversation:conversation:282727"},"id":"message:282727","revisionNum":1,"uid":282727,"depth":0,"board":{"__ref":"Tkb:board:TechnicalArticles"},"author":{"__ref":"User:user:321706"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"","metrics":{"__typename":"MessageMetrics","views":402},"postTime":"2017-02-08T10:00:00.000-08:00","lastPublishTime":"2017-02-08T10:00:00.000-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" As more organizations deploy IoT applications in their data centers and clouds, they're going to need their ADC to understand the unique protocols these devices use to communicate. \n\n In this Lightboard Lesson, I light up how IoT protocol MQTT (Message Queuing Telemetry Transport) works on BIG-IP v13. iRules allow you to do Topic based load balancing along with sensor authentication. And if you missed it, here is the #LBL on What is MQTT? \n\n \n\n ps \n\n Related: \n\n Lightboard Lessons: What is MQTT? Security Trends in 2016: Securing the Internet of Things The Intruders of Things The IoT Ready Platform Using F5 BIG-IP with IBM MessageSight ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"653","kudosSumWeight":0,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}}},"CachedAsset:text:en_US-components/community/Navbar-1744046271000":{"__typename":"CachedAsset","id":"text:en_US-components/community/Navbar-1744046271000","value":{"community":"Community Home","inbox":"Inbox","manageContent":"Manage Content","tos":"Terms of Service","forgotPassword":"Forgot Password","themeEditor":"Theme Editor","edit":"Edit Navigation Bar","skipContent":"Skip to content","migrated-link-9":"Groups","migrated-link-7":"Technical Articles","migrated-link-8":"DevCentral News","migrated-link-1":"Technical Forum","migrated-link-10":"Community Groups","migrated-link-2":"Water Cooler","migrated-link-11":"F5 Groups","Common-external-link":"How Do I...?","migrated-link-0":"Forums","article-series":"Article Series","migrated-link-5":"Community Articles","migrated-link-6":"Articles","security-insights":"Security Insights","migrated-link-3":"CrowdSRC","migrated-link-4":"CodeShare","migrated-link-12":"Events","migrated-link-13":"Suggestions"},"localOverride":false},"CachedAsset:text:en_US-components/community/NavbarHamburgerDropdown-1744046271000":{"__typename":"CachedAsset","id":"text:en_US-components/community/NavbarHamburgerDropdown-1744046271000","value":{"hamburgerLabel":"Side Menu"},"localOverride":false},"CachedAsset:text:en_US-components/community/BrandLogo-1744046271000":{"__typename":"CachedAsset","id":"text:en_US-components/community/BrandLogo-1744046271000","value":{"logoAlt":"Khoros","themeLogoAlt":"Brand Logo"},"localOverride":false},"CachedAsset:text:en_US-components/community/NavbarTextLinks-1744046271000":{"__typename":"CachedAsset","id":"text:en_US-components/community/NavbarTextLinks-1744046271000","value":{"more":"More"},"localOverride":false},"CachedAsset:text:en_US-components/authentication/AuthenticationLink-1744046271000":{"__typename":"CachedAsset","id":"text:en_US-components/authentication/AuthenticationLink-1744046271000","value":{"title.login":"Sign In","title.registration":"Register","title.forgotPassword":"Forgot Password","title.multiAuthLogin":"Sign In"},"localOverride":false},"CachedAsset:text:en_US-components/nodes/NodeLink-1744046271000":{"__typename":"CachedAsset","id":"text:en_US-components/nodes/NodeLink-1744046271000","value":{"place":"Place {name}"},"localOverride":false},"CachedAsset:text:en_US-components/tags/TagSubscriptionAction-1744046271000":{"__typename":"CachedAsset","id":"text:en_US-components/tags/TagSubscriptionAction-1744046271000","value":{"success.follow.title":"Following Tag","success.unfollow.title":"Unfollowed Tag","success.follow.message.followAcrossCommunity":"You will be notified when this tag is used anywhere across the community","success.unfollowtag.message":"You will no longer be notified when this tag is used anywhere in this place","success.unfollowtagAcrossCommunity.message":"You will no longer be notified when this tag is used anywhere across the community","unexpected.error.title":"Error - Action Failed","unexpected.error.message":"An unidentified problem occurred during the action you took. 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