87 research outputs found

    Security for the Industrial IoT: The Case for Information-Centric Networking

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    Industrial production plants traditionally include sensors for monitoring or documenting processes, and actuators for enabling corrective actions in cases of misconfigurations, failures, or dangerous events. With the advent of the IoT, embedded controllers link these `things' to local networks that often are of low power wireless kind, and are interconnected via gateways to some cloud from the global Internet. Inter-networked sensors and actuators in the industrial IoT form a critical subsystem while frequently operating under harsh conditions. It is currently under debate how to approach inter-networking of critical industrial components in a safe and secure manner. In this paper, we analyze the potentials of ICN for providing a secure and robust networking solution for constrained controllers in industrial safety systems. We showcase hazardous gas sensing in widespread industrial environments, such as refineries, and compare with IP-based approaches such as CoAP and MQTT. Our findings indicate that the content-centric security model, as well as enhanced DoS resistance are important arguments for deploying Information Centric Networking in a safety-critical industrial IoT. Evaluation of the crypto efforts on the RIOT operating system for content security reveal its feasibility for common deployment scenarios.Comment: To be published at IEEE WF-IoT 201

    Formal Verification of Synchronisation, Gossip and Environmental Effects for Wireless Sensor Networks

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    The Internet of Things (IoT) promises a revolution in the monitoring and control of a wide range of applications, from urban water supply networks and precision agriculture food production, to vehicle connectivity and healthcare monitoring. For applications in such critical areas, control software and protocols for IoT systems must be verified to be both robust and reliable. Two of the largest obstacles to robustness and reliability in IoT systems are effects on the hardware caused by environmental conditions, and the choice of parameters used by the protocol. In this paper we use probabilistic model checking to verify that a synchronisation and dissemination protocol for Wireless Sensor Networks (WSNs) is correct with respect to its requirements, and is not adversely affected by the environment. We show how the protocol can be converted into a logical model and then analysed using the probabilistic model-checker, PRISM. Using this approach we prove under which circumstances the protocol is guaranteed to synchronise all nodes and disseminate new information to all nodes. We also examine the bounds on synchronisation as the environment changes the performance of the hardware clock, and investigate the scalability constraints of this approach

    Formal verification of synchronisation, gossip and environmental effects for wireless sensor networks

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    The Internet of Things (IoT) promises a revolution in the monitoring and control of a wide range of applications, from urban water supply networks and precision agriculture food production, to vehicle connectivity and healthcare monitoring. For applications in such critical areas, control software and protocols for IoT systems must be verified to be both robust and reliable. Two of the largest obstacles to robustness and reliability in IoT systems are effects on the hardware caused by environmental conditions, and the choice of parameters used by the protocol. In this paper we use probabilistic model checking to verify that a synchronisation and dissemination protocol for Wireless Sensor Networks (WSNs) is correct with respect to its requirements, and is not adversely affected by the environment. We show how the protocol can be converted into a logical model and then analysed using the probabilistic model-checker, PRISM. Using this approach we prove under which circumstances the protocol is guaranteed to synchronise all nodes and disseminate new information to all nodes. We also examine the bounds on synchronisation as the environment changes the performance of the hardware clock, and investigate the scalability constraints of this approach. © 2019 Universitatsbibliothek TU Berlin

    The Internet of Robotic Things:A review of concept, added value and applications

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    The Internet of Robotic Things is an emerging vision that brings together pervasive sensors and objects with robotic and autonomous systems. This survey examines how the merger of robotic and Internet of Things technologies will advance the abilities of both the current Internet of Things and the current robotic systems, thus enabling the creation of new, potentially disruptive services. We discuss some of the new technological challenges created by this merger and conclude that a truly holistic view is needed but currently lacking.Funding Agency:imec ACTHINGS High Impact initiative</p

    LoRaWAN AS PART OF A SMART CITY STRATEGY

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    The LoRaWAN technology is repeatedly mentioned in connection with smart city initiatives, as it moves in the field of connectivity and IoT environment. This paper examines the role of LoRaWAN in smart city strategy and what vulnerabilities are known in the project using LoRaWAN. With help of a concrete use case of the city of Pforzheim (Germany), a SWOT model is set up and tested with experts. From this it can be deduced that the LoRaWAN technology is currently undergoing an interesting development but also has to overcome any hurdles in the urban environment

    Fog Computing in IoT Smart Environments via Named Data Networking: A Study on Service Orchestration Mechanisms

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    [EN] By offering low-latency and context-aware services, fog computing will have a peculiar role in the deployment of Internet of Things (IoT) applications for smart environments. Unlike the conventional remote cloud, for which consolidated architectures and deployment options exist, many design and implementation aspects remain open when considering the latest fog computing paradigm. In this paper, we focus on the problems of dynamically discovering the processing and storage resources distributed among fog nodes and, accordingly, orchestrating them for the provisioning of IoT services for smart environments. In particular, we show how these functionalities can be effectively supported by the revolutionary Named Data Networking (NDN) paradigm. Originally conceived to support named content delivery, NDN can be extended to request and provide named computation services, with NDN nodes acting as both content routers and in-network service executors. To substantiate our analysis, we present an NDN fog computing framework with focus on a smart campus scenario, where the execution of IoT services is dynamically orchestrated and performed by NDN nodes in a distributed fashion. A simulation campaign in ndnSIM, the reference network simulator of the NDN research community, is also presented to assess the performance of our proposal against state-of-the-art solutions. Results confirm the superiority of the proposal in terms of service provisioning time, paid at the expenses of a slightly higher amount of traffic exchanged among fog nodes.This research was partially funded by the Italian Government under grant PON ARS01_00836 for the COGITO (A COGnItive dynamic sysTem to allOw buildings to learn and adapt) PON Project.Amadeo, M.; Ruggeri, G.; Campolo, C.; Molinaro, A.; Loscri, V.; Tavares De Araujo Cesariny Calafate, CM. (2019). Fog Computing in IoT Smart Environments via Named Data Networking: A Study on Service Orchestration Mechanisms. Future Internet. 11(11):1-21. https://doi.org/10.3390/fi11110222S1211111Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431-440. doi:10.1016/j.bushor.2015.03.008Cicirelli, F., Guerrieri, A., Spezzano, G., Vinci, A., Briante, O., Iera, A., & Ruggeri, G. (2018). Edge Computing and Social Internet of Things for Large-Scale Smart Environments Development. IEEE Internet of Things Journal, 5(4), 2557-2571. doi:10.1109/jiot.2017.2775739Chiang, M., & Zhang, T. (2016). Fog and IoT: An Overview of Research Opportunities. IEEE Internet of Things Journal, 3(6), 854-864. doi:10.1109/jiot.2016.2584538Openfog Consortiumhttp://www.openfogconsortium.org/Zhang, L., Afanasyev, A., Burke, J., Jacobson, V., claffy, kc, Crowley, P., … Zhang, B. (2014). Named data networking. 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A., Molinaro, A., & Ruggeri, G. (2019). Gazing into the Crystal Ball: When the Future Internet Meets the Mobile Clouds. IEEE Transactions on Cloud Computing, 7(1), 210-223. doi:10.1109/tcc.2016.2573307Zhang, G., Li, Y., & Lin, T. (2013). Caching in information centric networking: A survey. Computer Networks, 57(16), 3128-3141. doi:10.1016/j.comnet.2013.07.007Yi, C., Afanasyev, A., Moiseenko, I., Wang, L., Zhang, B., & Zhang, L. (2013). A case for stateful forwarding plane. Computer Communications, 36(7), 779-791. doi:10.1016/j.comcom.2013.01.005Amadeo, M., Briante, O., Campolo, C., Molinaro, A., & Ruggeri, G. (2016). Information-centric networking for M2M communications: Design and deployment. Computer Communications, 89-90, 105-116. doi:10.1016/j.comcom.2016.03.009Tourani, R., Misra, S., Mick, T., & Panwar, G. (2018). Security, Privacy, and Access Control in Information-Centric Networking: A Survey. IEEE Communications Surveys & Tutorials, 20(1), 566-600. doi:10.1109/comst.2017.2749508Ndn-ace: Access Control for Constrained Environments over Named Data Networkinghttp://new.named-data.net/wp-content/uploads/2015/12/ndn-0036-1-ndn-ace.pdfZhang, Z., Yu, Y., Zhang, H., Newberry, E., Mastorakis, S., Li, Y., … Zhang, L. (2018). An Overview of Security Support in Named Data Networking. IEEE Communications Magazine, 56(11), 62-68. doi:10.1109/mcom.2018.1701147Cisco White Paperhttps://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-overview.pdfAazam, M., Zeadally, S., & Harras, K. A. (2018). Deploying Fog Computing in Industrial Internet of Things and Industry 4.0. IEEE Transactions on Industrial Informatics, 14(10), 4674-4682. doi:10.1109/tii.2018.2855198Hou, X., Li, Y., Chen, M., Wu, D., Jin, D., & Chen, S. (2016). Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures. IEEE Transactions on Vehicular Technology, 65(6), 3860-3873. doi:10.1109/tvt.2016.2532863Yousefpour, A., Fung, C., Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A., … Jue, J. P. (2019). All one needs to know about fog computing and related edge computing paradigms: A complete survey. Journal of Systems Architecture, 98, 289-330. doi:10.1016/j.sysarc.2019.02.009Baktir, A. C., Ozgovde, A., & Ersoy, C. (2017). How Can Edge Computing Benefit From Software-Defined Networking: A Survey, Use Cases, and Future Directions. IEEE Communications Surveys & Tutorials, 19(4), 2359-2391. doi:10.1109/comst.2017.2717482Duan, Q., Yan, Y., & Vasilakos, A. V. (2012). A Survey on Service-Oriented Network Virtualization Toward Convergence of Networking and Cloud Computing. IEEE Transactions on Network and Service Management, 9(4), 373-392. doi:10.1109/tnsm.2012.113012.120310Amadeo, M., Campolo, C., & Molinaro, A. (2016). NDNe: Enhancing Named Data Networking to Support Cloudification at the Edge. IEEE Communications Letters, 20(11), 2264-2267. doi:10.1109/lcomm.2016.2597850Krol, M., Marxer, C., Grewe, D., Psaras, I., & Tschudin, C. (2018). Open Security Issues for Edge Named Function Environments. IEEE Communications Magazine, 56(11), 69-75. doi:10.1109/mcom.2018.170111711801-2:2017 Information Technology—Generic Cabling for Customer Premiseshttps://www.iso.org/standard/66183.htm
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