An Asymmetric RSA-Based Security Approach for Opportunistic IoT

  • Nisha Kandhoul
  • Sanjay Kumar Dhurandher
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 27)


Internet of things (IoT) is a technical revolution of the internet where users, computing systems, and daily objects having sensing abilities collaborate to provide innovative services in various application domains. Opportunistic internet of things (OppIoT) is an extension of the opportunistic networks that exploits the interactions between the human-based communities and the IoT devices to increase the network connectivity and reliability. In this context, the security and privacy requirements play a crucial role as the collected information is exposed to a wide unknown audience. Traditional secure routing methods cannot be applied to OppIoT systems due to the lack of fixed path between nodes. Hence, an adaptable infrastructure is required to handle the security threats in dynamic OppIoT environment. This chapter proposes a novel security scheme for OppIoT using RSA-based asymmetric cryptography to secure the network and Markov chain to make prediction about a node’s future location and its corresponding delivery probability. Simulation results convey that the suggested approach ensures security of messages and outperforms the traditional protocols. RSASec is superior to LPFR-MC in terms of correct packet delivery by 19%, message delivery probability by 2.33%, number of messages dropped is reduced by 3.9%, and average latency is 6.76% lower than LPFR-MC.


Internet of things (IoT) Opportunistic networks (OppNet) Opportunistic internet of things (OppIoT) RSA Markov chain LPFR-MC Security Prophet Epidemic 


  1. 1.
    L. Atzori, A. Iera, G. Morabito, The internet of things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)CrossRefGoogle Scholar
  2. 2.
    B. Guo, D. Zhang, Z. Wang, Z. Yu, X. Zhou, Opportunistic IoT: exploring the harmonious interaction between human and the internet of things. J. Netw. Comput. Appl. 36(6), 1531–1539 (2013)CrossRefGoogle Scholar
  3. 3.
    D. Airehrour, J. Gutierrez, S.K. Ray, Secure routing for internet of things: a survey. J. Netw. Comput. Appl. 66, 198–213 (2016)CrossRefGoogle Scholar
  4. 4.
    Y. Zhang, S. Yuanyu, et al., On secure wireless communications for IoT under eaves-dropper collusion. IEEE Trans. Autom. Sci. Eng. 13(3), 1281–1293 (2016)CrossRefGoogle Scholar
  5. 5.
    X.-J. Lin, L. Sun, H. Qu, An efficient RSA-based certificateless public key encryption scheme. Discrete Appl. Math. 241, 39–47 (2018)MathSciNetCrossRefGoogle Scholar
  6. 6.
    S.K. Dhurandher, S.J. Borah, I. Woungang, A. Bansal, A. Gupta, A location prediction-based routing scheme for opportunistic networks in an IoT scenario, in Proceedings of Elsevier Journal of Parallel and Distributed Computing, 2017Google Scholar
  7. 7.
    P.L.R. Chze, K.S. Leong, A secure multi-hop routing for IoT communication, in Internet of Things (WF-IoT), 2014 IEEE World Forum on (IEEE, 2014)Google Scholar
  8. 8.
    X. Anita, J. Martin Leo Manickam, M.A. Bhagyaveni, Two-way acknowledgment-based trust framework for wireless sensor networks. Int. J. Distrib. Sens. Netw. 9(5), 952905 (2013)CrossRefGoogle Scholar
  9. 9.
    J. Montavont, D. Roth, T. Nol, Mobile IPv6 in internet of things: analysis, experimentations and optimizations. Ad Hoc Netw. 14, 1525 (2014)CrossRefGoogle Scholar
  10. 10.
    D.J. Malan, M. Welsh, M.D. Smith, A public-key infrastructure for key distribution in TinyOS based on elliptic curve cryptography, in Sensor and Ad Hoc Communications and Networks (IEEE, 2004), p. 7180Google Scholar
  11. 11.
    U. Hengartner, P. Steenkiste, Exploiting hierarchical identity-based encryption for access control to pervasive computing information, in SECURECOMM, 2005, p. 384396Google Scholar
  12. 12.
    L.B. Oliveira, M. Scott, J. Lopez, R. Dahab, TinyPBC: pairings for authenticated identity-based non-interactive key distribution in sensor networks, in INSS, 2008, p. 173180Google Scholar
  13. 13.
    N. Ye, Y. Zhu, R.-C.B. Wang, R. Malekian, Q.-M. Lin, An efficient authentication and access control scheme for perception layer of internet of things. Appl. Math. Inf. Sci. 8(4), 16171624 (2014)CrossRefGoogle Scholar
  14. 14.
    K. Graffi, P. Mukherjee, B. Menges, D. Hartung, A. Kovacevic, R. Steinmetz, Practical security in P2P-based social networks, in Proceeding of the IEEE 34th Conference Local Computer Networks, 2009, p. 269272Google Scholar
  15. 15.
    Z. Jia, X. Lin, S.-H. Tan, L. Li, Y. Yang, Public key distribution scheme for delay tolerant networks based on two-channel cryptography. J. Netw. Comput. Appl. 35(3), 905913 (2012)CrossRefGoogle Scholar
  16. 16.
    R. Lu, X. Lin, X. Liang, X. Shen, A secure handshake scheme with symptoms-matching for mHealthcare social network. J. Mobile Netw. Appl. 16(6), 683694 (2011)Google Scholar
  17. 17.
    Y. Ding, X.-W. Zhou, Z.-M. Cheng, W.-L. Zeng, Efficient authentication and key agreement protocol with anonymity for delay tolerant networks. Wireless Pers. Commun. 70(4), 14731485 (2013)Google Scholar
  18. 18.
    K. El Defrawy, J. Solis, G. Tsudik, Leveraging social contacts for message confidentiality in delay tolerant networks. in Proceedings of the 33rd Annual IEEE International Computer Software Applications Conference, 2009, p. 271279Google Scholar
  19. 19.
    Y. Gongjun, S. Olariu, M.C. Weigle, Providing location security in vehicular ad hoc networks. IEEE Wireless Commun. 16(6), 4855 (2009) Google Scholar
  20. 20.
    W. Wang, H. Man, Y. Liu, A framework for intrusion detection systems by social network analysis methods in ad hoc networks. Security Commun. Netw. 2(6), 669685 (2009)Google Scholar
  21. 21.
    L. Qinghua, Z. Sencun, C. Guohong, Routing in socially selfish delay tolerant networks, in Proceeding of the IEEE INFOCOM, 2010, p. 19Google Scholar
  22. 22.
    L. Pelusi, A. Passarella, M. Conti, Opportunistic networking: data forwarding in disconnected mobile ad hoc networks. IEEE Commun. Mag. 44(11), 134–141 (2006)CrossRefGoogle Scholar
  23. 23.
    A. Lindgren, A. Doria, D. Schelen, Probabilistic routing in intermittently connected networks, in Proceeding of ACM SIGMOBILE Mobile Comp. Commun., 2003, pp. 19–20Google Scholar
  24. 24.
    A. Keranen, J. Ott, T. Karkkainen, The ONE simulator for DTN protocol evaluation, in Proceeding of 2nd Intl. Conference on Simulation Tools and Techniques (SIMU-Tools’ 09), Rome, Italy, Mar 2–6, 2009, pp. 1–9Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nisha Kandhoul
    • 1
  • Sanjay Kumar Dhurandher
    • 2
  1. 1.CAITFS, Division of Information Technology NSITUniversity of DelhiNew DelhiIndia
  2. 2.CAITFS, Department of Information TechnologyNetaji Subhas University of TechnologyNew DelhiIndia

Personalised recommendations