Skip to main content
SpringerLink
Log in

Dynamic and comprehensive trust model for IoT and its integration into RPL

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Ensuring security in IoT routing protocols is more challenging due to the fact that devices are mobile, resource constrained, and heterogeneous. The routing protocol for low-power and lossy networks (RPL) as the de facto routing protocol for IoT provides a little protection against routing attacks. On the other hand, the standard RPL because of the use of a single metric in routing has limitations that ultimately results in loss of network performance. To overcome the limitations of the use of a single metric and to prevent the consequences of routing attacks, we used the concept of trust and propose dynamic and comprehensive trust model for IoT (DCTM-IoT) and integrate it into RPL (DCTM-RPL). We provide a comprehensive hierarchical model for trusting of things in IoT, which has a multi-dimensional vision of trust. We put the combination of metrics and necessary activities to deal with attacks under the umbrella of trust level calculation. The performance of DCTM-RPL is compared with the standard RPL protocol in mobile environment and under routing major attacks. DCTM-RPL demonstrates its superior performance over the standard RPL protocol in the detection and isolation attacks. The DCTM-RPL, in addition to resistance mitigating routing attacks, improves network performance.

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
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Kang M, Na O, Chang H (2016) Evaluation of groundwater quality in a rural community in North Central of Nigeria. J Supercomput 72:103. https://doi.org/10.1007/s11227-015-1490-0

    Article  Google Scholar 

  2. Koo C, Kim J (2018) Enforcing high-level security policies for Internet of Things. J Supercomput 74:4497. https://doi.org/10.1007/s11227-017-2201-9

    Article  Google Scholar 

  3. Borujeni EM, Rahbari D, Nickray M (2018) Fog-based energy-efficient routing protocol for wireless sensor networks. J Supercomput. https://doi.org/10.1007/s11227-018-2514-3

  4. Sharma D, Ojha A, Bhondekar AP (2018) Heterogeneity consideration in wireless sensor networks routing algorithms: a review. J Supercomput. https://doi.org/10.1007/s11227-018-2635-8

  5. Winter T, Thubert P, Brandt A, Hui JW, Kelsey R, Levis P, Pister KS, Struik R, Vasseur J, Alexander RK (2012) RPL: IPv6 routing protocol for low-power and lossy networks. RFC 6550:1–157

    Google Scholar 

  6. Tseng F, Chou L, Chao H (2011) A survey of black hole attacks in wireless mobile ad hoc networks. Hum Cent Comput Inf Sci 1:1–16

    Article  Google Scholar 

  7. Gaddour O, Koubaa A, Baccour N, Abid M (2014) OF-FL: QoS-aware fuzzy logic objective function for the RPL routing protocol. In: 2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), pp 365–372

  8. Gaddour O, Koubaa A (2012) RPL in a nutshell: a survey. Comput Netw 56:3163–3178

    Article  Google Scholar 

  9. Vasseur J, Kim M, Pister KS, Dejean N, Barthel D (2012) Routing metrics used for path calculation in low-power and lossy networks. RFC 6551:1–30

    Google Scholar 

  10. Thubert P (2012) Objective function zero for the routing protocol for low-power and lossy networks (RPL). RFC 6552:1–14

    Google Scholar 

  11. Gnawali O, Levis P (2012) Internet engineering task force (ietf) the minimum rank with hysteresis objective function

  12. Lamaazi H, Benamar N (2018) OF-EC: a novel energy consumption aware objective function for RPL based on fuzzy logic. J Netw Comput Appl 117:42–58

    Article  Google Scholar 

  13. Sharkawy B, Khattab A, Elsayed KM (2014) Fault-tolerant RPL through context awareness. In: 2014 IEEE World Forum on Internet of Things (WF-IoT), pp 437–441

  14. Gaddour O, Koubaa A, Abid M (2015) Quality-of-service aware routing for static and mobile IPv6-based low-power and lossy sensor networks using RPL. Adhoc Netw 33:233–256

    Google Scholar 

  15. Kharrufa H, Al-Kashoash HA, Kemp AH (2018) A game theoretic optimization of RPL for mobile Internet of Things applications. IEEE Sens J 18:2520–2530

    Article  Google Scholar 

  16. Karkazis P, Leligou H, Sarakis L, Zahariadis TB, Trakadas P, Velivassaki TH, Capsalis CN (2012) Design of primary and composite routing metrics for RPL-compliant wireless sensor networks. Int Conf Telecommun Multimed (TEMU) 2012:13–18

    Article  Google Scholar 

  17. Hong K, Choi L (2011) DAG-based multipath routing for mobile sensor networks. ICTC 2011:261–266

    Google Scholar 

  18. Airehrour D, Gutierrez JA, Ray SK (2018) SecTrust-RPL: a secure trust-aware RPL routing protocol for Internet of Things. Future Gener Comput Syst. https://doi.org/10.1016/j.future.2018.03.021

  19. Djedjig N, Tandjaoui D, Medjek F (2015) Trust-based RPL for the Internet of Things. In: 2015 IEEE Symposium on Computers and Communication (ISCC), pp 962–967

  20. Djedjig N, Tandjaoui D, Medjek F, Romdhani I (2017) New trust metric for the RPL routing protocol. In: 2017 8th International Conference on Information and Communication Systems (ICICS), pp 328–335

  21. Iuchi K, Matsunaga T, Toyoda K, Sasase I (2015) Secure parent node selection scheme in route construction to exclude attacking nodes from RPL network. In: 2015 21st Asia-Pacific Conference on Communications (APCC), pp 299–303

  22. Seeber S, Sehgal A, Stelte B, Rodosek GD, Schnwlder J (2013) Towards a trust computing architecture for RPL in cyber physical systems. In: Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013), pp 134–137

  23. Guclu SO, Ozcelebi T, Lukkien JJ (2016) Trust-based neighbor unreachability detection for RPL. In: 2016 25th International Conference on Computer Communication and Networks (ICCCN), pp 1–6

  24. Mayzaud A, Badonnel R, Chrisment I (2016) A taxonomy of attacks in RPL-based Internet of Things. Int J Netw Secur 18:459–473

    Google Scholar 

  25. Frigyik BA, Kapila A, Gupta MR (2010) Introduction to the Dirichlet distribution and related processes

  26. Zhang W, Zhu S, Tang J et al (2018) A novel trust management scheme based on Dempster–Shafer evidence theory for malicious nodes detection in wireless sensor networks. J Supercomput 74:1779. https://doi.org/10.1007/s11227-017-2150-3

    Article  Google Scholar 

  27. Mui L, Mohtashemi M (2001) A computational model of trust and reputation. In: Proceedings of the 35th Annual Hawaii International Conference on System Sciences, HICSS

  28. Bernab JB, Ramos JL, Gmez-Skarmeta AF (2016) TACIoT: multidimensional trust-aware access control system for the Internet of Things. Soft Comput 20:1763–1779

    Article  Google Scholar 

  29. Dunkels A, Schmidt O, Finne N, Eriksson J, sterlind F, Tsiftes N, Durvy M (2011) The Contiki OS: the operating system for the Internet of Things. http://www.contiki-os.org. Accessed 01 Sept 2018

  30. Aschenbruck N, Ernst R, Gerhards-Padilla E, Schwamborn M (2010) BonnMotion: a mobility scenario generation and analysis tool. In: SimuTools

  31. Baccour N, Koubaa A, Jama MB, Youssef H, Zuniga M, Alves M (2009) A comparative simulation study of link quality estimators in wireless sensor networks. In: 2009 IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, pp 1–10

Download references

Author information

Authors and Affiliations

  1. Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran

    Seyyed Yasser Hashemi & Fereidoon Shams Aliee

Authors
  1. Seyyed Yasser Hashemi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fereidoon Shams Aliee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fereidoon Shams Aliee.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hashemi, S.Y., Shams Aliee, F. Dynamic and comprehensive trust model for IoT and its integration into RPL. J Supercomput 75, 3555–3584 (2019). https://doi.org/10.1007/s11227-018-2700-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-018-2700-3

Keywords

Search

Navigation