Skip to main content
SpringerLink
Log in

Towards a Light Weight Routing Security in IoT Using Non-cooperative Game Models and Dempster–Shaffer Theory

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The internet of things (IoT) has become an emerging technology owing to the rapidly increasing number of devices and their connectivity to the internet. Routing protocol for low-power and lossy networks (RPL) is a predominant routing protocol for the IoT. The RPL routing embraces the distance to the gateway node as a rank for parent selection and builds the destination oriented directed acyclic graph (DODAG). The malicious nodes utilize the advantage of low rank based parent selection to involve in data forwarding. However, the malicious node behavior and the harsh channel conditions due to the collision are equally considered as malicious in the existing detection mechanisms. In addition, most of the routing solutions exploit the traditional schemes for IoT security, but not considering the adaptability to IoT routing specifications. Thus, this work attempts to integrate the DODAG-specific contextual trust model, and RPL-specific rank variance factor, named as Secure RPL using non-cooperative game MOdels and DEmpster Shaffer Theory in IoT (S-MODEST), such that it can detect the attackers accurately and significantly reduces the resource consumption. The non-cooperative game model consists of two interrelated formulations in the proposed solution. Firstly, non-zero sum game constructs the trust model and extracts the contextual information from DODAG structure to strengthen the trustworthiness. Secondly, the evolutionary game is utilized for trusted router selection. The non-zero sum game theory formulates the interaction of nodes and assists the trust measurement by applying direct and restricted Dempster–Shaffer theory. The DODAG-specific contextual trust evaluation differentiates the collision dropping from the undesirable scenarios and supports the nodes in building a highly trusted DODAG structure to the gateway using multiplicative trust factor. To enforce the routing cooperation of selfish nodes and differentiate malicious nodes, the evolutionary game model embraces the node trust, which is measured using non-zero sum game model. As a result, the non-cooperative game models enable the S-MODEST to precisely select a secure route as well as to maintain the routing performance effectively. The simulation results demonstrate that the detection accuracy and throughput of the proposed context-aware noncooperative game theory based trust model are substantially higher and outperform the existing SecTrust.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer Networks,54(15), 2787–2805.

    Article  Google Scholar 

  2. Whitmore, A., Agarwal, A., & Da Xu, L. (2015). The internet of things: A survey of topics and trends”. Information Systems Frontiers,17(2), 261–274.

    Article  Google Scholar 

  3. Evans, D. (2011). The internet of things: How the next evolution of the internet is changing everything. CISCO white paper, 2011.

  4. Sicari, S., Rizzardi, A., Grieco, L. A., & Coen-Porisini, A. (2015). Security, privacy, and trust in internet of things: The road ahead. Computer Networks,76, 146–164.

    Article  Google Scholar 

  5. Lin, J., et al. (2017). A survey on Internet of things: Architecture, enabling technologies, security, and privacy, and applications”. IEEE Internet of Things Journal,4(1125), 1142.

    Google Scholar 

  6. Olivier, F., Carlos, G., & Florent, N. (2015). New security architecture for IoT network. Procedia Computer Science,52, 1028–1033.

    Article  Google Scholar 

  7. Uanjie, L., Hongyun, X., Qiying, C., Zichuan, L., & Shigen, S. (2015). Evolutionary game-based trust strategy adjustment among nodes in wireless sensor networks. International Journal of Distributed sensor Networks,11, 818903.

    Article  Google Scholar 

  8. Abdalzaher, Mohamed S., Seddik, Karim, Elsabrouty, Maha, Muta, Osamu, Furukawa, Hiroshi, & Abdel-Rahman, Adel. (2016). Game theory meets wireless sensor networks security requirements and threats mitigation: A survey. Sensors,16(7), 1003.

    Article  Google Scholar 

  9. Nguyen, Kim Thuat, Laurent, Maryline, & Oualha, Nouha. (2015). Survey on secure communication protocols for the internet of things. Ad Hoc Networks,32, 17–31.

    Article  Google Scholar 

  10. Sridipta, Misra, Maheswaran, Muthucumaru, & Hashmi, Salman. (2016). Securing internet of things. Berlin: Springer.

    Google Scholar 

  11. Winter, T., Thubert, P., Brandt, A. et al. (2011). RPL: IPv6 routing protocol for low power and lossy networks. Draft-ietf-rollrpl-19, 1–165.

  12. Gaddoura, O., & Koubaa, A. (2012). RPL in a nutshell: A survey. Computer Networks,56(14), 3163–3178.

    Article  Google Scholar 

  13. Le, A. et al. (2013). The impacts of internal threats towards routing protocol for low power and lossy network performance. In IEEE symposium on computers and communications.

  14. Grgic, K., Krizanovic Cik, V., & Mandrić Radivojevic, V. (2016). Security aspects of IPv6-based wireless sensor networks. International Journal of Electrical and Computer Engineering Systems,7(1), 29–37.

    Google Scholar 

  15. Adat, V., & Gupta B. B. (2017). Security in internet of things: Issues, challenges, taxonomy, and architecture. International Telecommunication Systems, 67(3), 423–441.

    Article  Google Scholar 

  16. Airehrour, D., Gutierrez, J., & Ray, S. K. (2016). Secure routing for internet of things: A survey. Journal of Network and Computer Applications,66, 198–213.

    Article  Google Scholar 

  17. Yan, Z., Zhang, P., & Vasilakos, A. V. (2014). A survey on trust management for internet of things. Journal of network and computer applications,42, 120–134.

    Article  Google Scholar 

  18. Yang, Y., et al. (2017). A survey on security and privacy issues in internet-of-things. IEEE Internet of Things Journal,4, 1250–1258.

    Article  Google Scholar 

  19. Jing, Q., et al. (2014). Security of the internet of things: Perspective and challenges. Wireless Networks,20(8), 2481–2501.

    Article  Google Scholar 

  20. Shahid, R., & Linus, W. (2013). SVELTE: Real-time intrusion detection in the internet of Things. Ad Hoc Networks,11(8), 2661–2674.

    Article  Google Scholar 

  21. Chze, P., & Leong, K. S. (2014). A secure multi-hop routing for IoT communication. In International IEEE world forum on internet of things (WF-IoT) (pp. 428–432).

  22. Krentz, K.-F., Rafiee, H., & Meinel, C. (2013). 6LoWPAN security: Adding compromise resilience to the 802.15.4 security sublayer. In Presented at the proceedings of the international workshop on adaptive security, Zurich.

  23. Anita, X., Bhagyaveni, M., & Manickam, J. M. L. (2015). Collaborative lightweight trust management scheme for wireless sensor networks. Wireless Personal Communications,80(1), 117–140.

    Article  Google Scholar 

  24. Granjal, J., Monteiro, E., & Silva, J. S. (2015). Security for the internet of things: A survey of existing protocols and open research issues. IEEE Communications Surveys and Tutorials,17(3), 1294–1312.

    Article  Google Scholar 

  25. Duan, J., Gao, D., Yang, D., Foh, C. H., & Chen, H. H. (2014). An energy-aware trust derivation scheme with game theoretic approach in wireless sensor networks for IoT applications. IEEE Internet of Things Journal,1(1), 58–69.

    Article  Google Scholar 

  26. Feng, R., Che, S., Wang, X., & Wan, J. (2014). An incentive mechanism based on game theory for trust management. Security and Communication Networks,7, 2318–2325.

    Article  Google Scholar 

  27. Ding, Y., Zhou, X. W., Cheng, Z. M., & Lin, F. H. (2013). A security differential game model for sensor networks in context of the internet of things. Wireless Personal Communications,72(1), 375–388.

    Article  Google Scholar 

  28. Saled, Y. B., et al. (2013). Trust management system design for the internet of things: A context-aware and multi-service approach. Computers and Security,39, 361–365.

    Google Scholar 

  29. Cervantes, C. et al. (2015). Detection of sinkhole attacks for supporting secure routing on 6LoWPAN for internet of things. In IFIP/IEEE international symposium on integrated network management.

  30. Mayzaud, A., Badonnel, R., & Chrisment, I. (2016). A taxonomy of attacks in RPL-based internet of things. International Journal of Network Security,18(3), 459–473.

    Google Scholar 

  31. Nitti, M., Girau, R., & Atzori, L. (2014). Trustworthiness management in the social internet of things. IEEE Transactions of Knowledge and Data engineering,26(5), 1253–1266.

    Article  Google Scholar 

  32. Lai, G. H. (2016). Detection of wormhole attacks on IPv6 mobility-based wireless sensor network. EURASIP Journal on Wireless Communications and Networking,1, 274.

    Article  Google Scholar 

  33. Chen, C., Hsu, S., & Lai, G. (2016). Defense denial-of-service attacks on IPv6 wireless sensor networks. In T. Zin, J. W. Lin, J. S. Pan, P. Tin, M. Yokota (Eds.), International genetic and evolutionary computing. Advances in Intelligent Systems and Computing. (vol. 387, pp. 319–326). Cham: Springer.

    Google Scholar 

  34. Airehrour, D., Gutierrez, J., & Ray, S. K. (2016). A lightweight trust design for IoT routing. In Dependable, autonomic and secure computing, 14th international conference on pervasive intelligence and computing, 2nd IEEE international conference on big data intelligence and computing and cyber science and technology congress (pp. 552–557).

  35. Jøsang, A., Hayward, R. & Pope, S. (2006). Trust network analysis with subjective logic. In Proceedings of the 29th Australasian computer science conference (Vol. 48).

Download references

Acknowledgements

I would like to thanks my supervisor Dr. Shaveta Rani for her extremely useful support in this research. On the same time, Dr. Paramjeet Singh helps in the publication with their experience.

Author information

Authors and Affiliations

  1. MRSPTU University, Bathinda, India

    Vidhu Kiran, Shaveta Rani & Paramjeet Singh

Authors
  1. Vidhu Kiran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shaveta Rani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paramjeet Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vidhu Kiran.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kiran, V., Rani, S. & Singh, P. Towards a Light Weight Routing Security in IoT Using Non-cooperative Game Models and Dempster–Shaffer Theory. Wireless Pers Commun 110, 1729–1749 (2020). https://doi.org/10.1007/s11277-019-06809-w

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-019-06809-w

Keywords

Search

Navigation