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Secured Data Gathering Protocol for IoT Networks

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10879))

Abstract

Data collection in Wireless Sensor Networks (WSN) and specifically in the Internet of Things (IoT) networks draws significant attention both by the industrial and academic communities. Numerous Medium Access Control (MAC) protocols for WSN have been suggested over the years, designed to cope with a variety of setups and objectives. However, most IoT devices are only required to exchange very little information (typically one out of several predetermined messages), and do so only sporadically. Furthermore, only a small subset (which is not necessarily known a priori) intends to transmit at any given time. Accordingly, a tailored protocol is much more suited than the existing general purpose WSN protocols. In many IoT applications securing the data transmitted and the identity of the transmitting devices is critical. However, security in such IoT networks is highly challenging since the devices are typically very simple, with highly constrained capabilities, e.g., limited memory and computational power or no sophisticated algorithmic capabilities, which make the utilization of complex cryptographic primitives unfeasible. Furthermore, note that in many such applications, securing the information transmitted is not sufficient, since knowing the transmitters identity conveys a lot of information (e.g., the identity of a hazard detector conveys the information that a threat was detected).

In this paper, we design and analyze an efficient secure data collection protocol based on information theoretic principles, in which an eavesdropper observing only partial information sent on the channel cannot gain significant information on the transmitted messages or even on the identity of the devices that sent these messages. In the suggested protocol, the sink collects messages from up to K sensors simultaneously, out of a large population of sensors, without knowing in advance which sensors will transmit, and without requiring any synchronization, coordination or management overhead. In other words, neither the sink nor the other sensors need to know who are the actively transmitting sensors, and this data is decoded directly from the channel output. We provide a simple secure codebook construction with very efficient and simple encoding and decoding procedures.

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References

  1. Shipley, A.: Security in the internet of things, lessons from the past for the connected future. Security Solutions, Wind River, White Paper (2013)

    Google Scholar 

  2. Díaz, M., Martín, C., Rubio, B.: State-of-the-art, challenges, and open issues in the integration of internet of things and cloud computing. J. Netw. Comput. Appl. 67, 99–117 (2016)

    Article  Google Scholar 

  3. Zhou, J., Cao, Z., Dong, X., Vasilakos, A.V.: Security and privacy for cloud-based iot: Challenges. IEEE Commun. Mag. 55(1), 26–33 (2017)

    Article  Google Scholar 

  4. Mehmood, Y., Ahmad, F., Yaqoob, I., Adnane, A., Imran, M., Guizani, S.: Internet-of-things-based smart cities: recent advances and challenges. IEEE Commun. Mag. 55(9), 16–24 (2017)

    Article  Google Scholar 

  5. Chan, C.L., Jaggi, S., Saligrama, V., Agnihotri, S.: Non-adaptive group testing: explicit bounds and novel algorithms. IEEE Trans. Inf. Theory 60(5), 3019–3035 (2014)

    Article  MathSciNet  Google Scholar 

  6. Polastre, J., Hill, J., Culler, D.: Versatile low power media access for wireless sensor networks. In: Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (SenSys), pp. 95–107. ACM (2004)

    Google Scholar 

  7. Ye, W., Heidemann, J., Estrin, D.: An energy-efficient MAC protocol for wireless sensor networks. In: Proceedings of IEEE Twenty-First Annual Joint Conference of the IEEE computer and communications societies, INFOCOM 2002, vol. 3, pp. 1567–1576. IEEE (2002)

    Google Scholar 

  8. Huang, P., Xiao, L., Soltani, S., Mutka, M.W., Xi, N.: The evolution of MAC protocols in wireless sensor networks: a survey. IEEE Commun. Surv. Tutor. 15(1), 101–120 (2013)

    Article  Google Scholar 

  9. Lin, J., Ingram, M.A.: SCT-MAC: a scheduling duty cycle MAC protocol for cooperative wireless sensor network. In: 2012 IEEE International Conference on Communications (ICC), pp. 345–349. IEEE (2012)

    Google Scholar 

  10. Liu, C.-J., Huang, P., Xiao, L.: TAS-MAC: a traffic-adaptive synchronous MAC protocol for wireless sensor networks. ACM Trans. Sens. Netw. (TOSN) 12(1), 1 (2016)

    Article  Google Scholar 

  11. Kakria, A., Aseri, T.C.: Survey of synchronous MAC protocols for Wireless Sensor Networks. In: 2014 Recent Advances in Engineering and Computational Sciences (RAECS), pp. 1–4. IEEE (2014)

    Google Scholar 

  12. Buettner, M., Yee, G.V., Anderson, E., Han, R.: X-MAC: a short preamble MAC protocol for duty-cycled wireless sensor networks. In: Proceedings of the 4th International Conference on Embedded Networked Sensor Systems (SenSys), pp. 307–320. ACM Press, New York (2006)

    Google Scholar 

  13. Sun, Y., Gurewitz, O., Johnson, D.B.: RI-MAC: a receiver-initiated asynchronous duty cycle MAC protocol for dynamic traffic loads in wireless sensor networks. In: Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (SenSys), pp. 1–14. ACM (2008)

    Google Scholar 

  14. Tang, L., Sun, Y., Gurewitz, O., Johnson, D.B.: EM-MAC: a dynamic multichannel energy-efficient MAC protocol for wireless sensor networks. In: Proceedings of the Twelfth ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), p. 23. ACM (2011)

    Google Scholar 

  15. Dorfman, R.: The detection of defective members of large populations. Ann. Math. Stat. 14(4), 436–440 (1943)

    Article  Google Scholar 

  16. Rom, R., Sidi, M.: Multiple Access Protocols: Performance and Analysis. Springer, New York (1990). https://doi.org/10.1007/978-1-4612-3402-9

    Book  MATH  Google Scholar 

  17. Cohen, A., Cohen, A., Gurewitz, O.: Data aggregation over multiple access wireless sensors networks. arXiv preprint (2017)

    Google Scholar 

  18. Atia, G.K., Saligrama, V.: Boolean compressed sensing and noisy group testing. IEEE Trans. Inf. Theory 58(3), 1880–1901 (2012). A minor corection appered in, vol. 61, no. 3, p. 1507, 2015

    Article  MathSciNet  Google Scholar 

  19. Sejdinovic, D., Johnson, O.: Note on noisy group testing: asymptotic bounds and belief propagation reconstruction. In: 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp. 998–1003. IEEE (2010)

    Google Scholar 

  20. Bloch, M., Barros, J.: Physical-Layer Security: From Information Theory to Security Engineering. Cambridge University Press, Cambridge (2011)

    Book  Google Scholar 

  21. Cohen, A., Cohen, A., Jaggi, S., Gurewitz, O.: Secure group testing. arXiv:1607.04849 (2016)

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Acknowledgment

This research was partially supported by the Israeli MOITAL NEPTUN consortium and in part by the European Union Horizon 2020 Research and Innovation Programme SUPERFLUIDITY under Grant 671566.

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Correspondence to Alejandro Cohen , Asaf Cohen or Omer Gurewitz .

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Cohen, A., Cohen, A., Gurewitz, O. (2018). Secured Data Gathering Protocol for IoT Networks. In: Dinur, I., Dolev, S., Lodha, S. (eds) Cyber Security Cryptography and Machine Learning. CSCML 2018. Lecture Notes in Computer Science(), vol 10879. Springer, Cham. https://doi.org/10.1007/978-3-319-94147-9_11

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  • DOI: https://doi.org/10.1007/978-3-319-94147-9_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94146-2

  • Online ISBN: 978-3-319-94147-9

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