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An efficient method for group key management in Internet of Things using machine learning approach

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Abstract

Internet of Things (IoT) represent a network of pervasive devices with different characteristics and features. It is important to provide security in IoT as Internet plays a prominent role in the communication process. In this paper, a novel group and hierarchical group key management scheme is proposed. The devices are found into groups and placed into various levels of hierarchy. The group leader shares a key to the members in the group and the key needs to be updated based on the entry and exit of the members into and out of the groups. Also, the machine learning techniques are used to make the system adapt to the provision of the keys to the devices which enter into the group. Incremental Gaussian Mixture Model is used to determine whether the particular device belong to the group or not. The proposed algorithm, machine learning based group and hierarchical key management is simulated and compared with the group and hierarchical key management scheme for solving security problems in IoT in terms of throughput and delay with varying no. of groups and overall cost with respect to no. of nodes and mobility speed.

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References

  1. OWASP (2013) Top 10 2017: the ten most critical web application security risks. Sl: The OWASP Foundation

  2. Abomhara M, Koien GM (2014) Security and privacy in the Internet of Things: current status and open issues. In: International conference on privacy and security in mobile systems (PRISMS), pp 1–8

  3. Atzori L, Iera A, Morabito G (2010) The Internet of Things: a survey. Comput Netw 54(15):2787–2805

    Article  Google Scholar 

  4. Gubbia J, Buyyab R, Marusic S, Palaniswami M (2013) Internet of Things (IoT): a vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645–1660

    Article  Google Scholar 

  5. Li X, Lu R, Liang X, Shen X (2011) Smart community: an Internet of Things application. IEEE Commun Mag 49(11):68–75

    Article  Google Scholar 

  6. Firner B, Moore RS, Howard R, Martin RP, Zhang Y (2011) Poster: smart buildings, sensor networks, and the Internet of Things. In: Proceedings of ACM conference on embedded networked sensor systems, Nov 2011, pp 337–338

  7. Sheng Z, Yang S, Yu Y, Vasilakos A (2013) A survey on the IETF protocol suite for the Internet of Things: standards, challenges, and opportunities. IEEE Wirel Commun 20(6):91–98

    Article  Google Scholar 

  8. Andrea I, Chrysostomou C, Hadjichristofi G (2015) Internet of Things: security vulnerabilities and challenges. In: Proceedings of IEEE symposium on computers and communication, Larnaca, Cyprus, Feb 2015, pp 180–187

  9. Roman R, Zhou J, Lopez J (2013) On the features and challenges of security and privacy in distributed Internet of Things. Comput Netw 57(10):2266–2279

    Article  Google Scholar 

  10. Chen S, Xu H, Liu D, Hu B (2014) A vision of IoT: applications, challenges, and opportunities with china perspective. IEEE Internet Things J 1(4):349–359

    Article  Google Scholar 

  11. Zhou J, Cao Z, Dong X, Vasilakos AV (2017) Security and privacy for cloud-based IoT: challenges. IEEE Commun Mag 55(1):26–33

    Article  Google Scholar 

  12. Suo H, Wan J, Zou C, Liu J (2012) Security in the Internet of Things: a review. In: Computer science and electronics engineering (ICCSEE), pp 648–651

  13. Zhang Y (2011) Technology framework of the Internet of Things and its application. In: Electrical and control engineering (ICECE), pp 4109–4112

  14. Yang Xue, Li Zhihua, Geng Zhenmin, Zhang Haitao (2012) A multilayer security model for Internet of Things. Commun Comput Inf Sci 312:388–393

    Google Scholar 

  15. Khan R, Khan SU, Zaheer R, Khan S (2012) Future internet: the Internet of Things architecture, possible applications and key challenges. In: 10th international conference on frontiers of information technology (FIT 2012), pp 257–260

  16. Shi Y-r, Hou T (2013) Internet of Things key technologies and architectures research in information processing. In: Proceedings of the 2nd international conference on computer science and electronics engineering (ICCSEE)

  17. Mahalle PN, Anggorojati B, Prasad NR, Prasad R (2013) Identity authentication and capability based access control (IACAC) for the Internet of Things. J Cyber Secur Mobil 1:309–348

    Google Scholar 

  18. Leo M, Battisti F, Carli M, Neri A (2014) A federated architecture approach for Internet of Things security. In: Euro Med Telco conference (EMTC), pp 1–5

  19. Xiao L, Wan X, Lu X, Zhang Y, Wu D (2018) IoT security techniques based on machine learning: how do IoT devices use AI to enhance security? IEEE Signal Process Mag 35(5):41–49

    Article  Google Scholar 

  20. Ling Z, Liu K, Xu Y, Gao C, Jin Y, Zou C, Zhao W et al (2018) IoT security: an end-to-end view and case study. arXiv:1805.05853

  21. Lally G, Sgandurra D (2018) Towards a framework for testing the security of IoT devices consistently. In: International workshop on emerging technologies for authorization and authentication, September 2018, Springer, Cham, pp 88–102

  22. Sivaraman V, Gharakheili HH, Vishwanath A, Boreli R, Mehani O (2015) Network-level security and privacy control for smart-home IoT devices. In: 2015 IEEE 11th international conference on wireless and mobile computing, networking and communications (WiMob), IEEE, October 2015, pp 163–167

  23. Porambage P, Braeken A, Schmitt C, Gurtov A, Ylianttila M, Stiller B (2015) Group key establishment for enabling secure multicast communication in wireless sensor networks deployed for IoT applications. IEEE Access 3:1503–1511

    Article  Google Scholar 

  24. Keoh S, Kumar S, Gracia-Morchon O, Dijk E, Rahman A (2014) DTLS-based multicast security for low-power and lossy networks (LLNs). draft-keoh-dice-multicast-security-05, IETF work in progress, February 2014

  25. Kothmayr C, Schmitt W, Hu M Brunig, Carle G (2013) DTLS based security and two-way authentication for the Internet of Things. Ad Hoc Netw Elsevier 11(8):2710–2723

    Article  Google Scholar 

  26. Xiao L, Li Y, Han G, Liu G, Zhuang W (2016) PHY-layer spoofing detection with reinforcement learning in wireless networks. IEEE Trans Veh Technol 65(12):10037–10047

    Article  Google Scholar 

  27. Xiao L, Wan X, Han Z (2018) PHY-layer authentication with multiple landmarks with reduced overhead. IEEE Trans Wireless Commun 17(3):1676–1687

    Article  Google Scholar 

  28. Engel PM, Heinen MR (2010) Incremental learning of multivariate gaussian mixture models. In: Brazilian symposium on artificial intelligence, Springer, Berlin, Heidelberg, October 2010, pp 82–91

  29. Shi C, Liu J, Liu H, Chen Y (2017) Smart user authentication through actuation of daily activities leveraging WiFi-enabled IoT. In: Proceedings of ACM international symposium on mobile ad hoc networking and computing (MobiHoc), Chennai, India, Jul 2017, pp 1–10

  30. Karrothu A, Norman J (2018) Group and hierarchical key management for secure communications in IoT. Int J Commun Syst Wiley Publ. https://doi.org/10.1002/dac.3859

    Article  Google Scholar 

  31. Dunkels A, Bjorn G, Voigt T (2004) Contiki-a lightweight and flexible operating system for tiny networked sensors. In: 29th annual IEEE international conference on local computer networks, IEEE 2004, pp 455–462

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Correspondence to Jasmine Norman.

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Karrothu, A., Norman, J. An efficient method for group key management in Internet of Things using machine learning approach. Evol. Intel. 14, 445–452 (2021). https://doi.org/10.1007/s12065-019-00258-x

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