Skip to main content
Log in

PL-IDS: physical layer trust based intrusion detection system for wireless sensor networks

  • Original Research
  • Published:
International Journal of Information Technology Aims and scope Submit manuscript

Abstract

In this paper, a physical layer trust based intrusion detection system (PL-IDS) is proposed to calculate the trust for wireless sensor networks (WSNs) at the physical layer. The trust value of sensor node is calculated as per the deviation of key factors at the physical layer. The proposed scheme is effective to identify the abnormal nodes in WSNs. The abnormal nodes mainly attack the physical layer by denial of service attack. They use the jamming attack by consuming the resources of the genuine nodes, which leads to a denial of service. To analyze the performance of PL-IDS, we have implemented the periodic jamming attack. Results show that PL-IDS performs better in terms of false alarm rate and malicious node detection accuracy rate.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Estrin D, Govindan R, Heidemann J, Kumar S (1999) Next century challenges: scalable coordination in sensor networks. In: The 5th annual ACM/IEEE international conference on mobile computing and networking, ACM/IEEE, pp 263–270

  2. Bhasin V, Kumar S, Saxena P, Katti C (2018) Security architectures in wireless sensor network. Int J Inf Process. https://doi.org/10.1007/s41870-018-0103-6

    Google Scholar 

  3. Mehra P, Doja M, Alam B (2017) Zonal based approach for clustering in heterogeneous WSN. Int J Inf Process. https://doi.org/10.1007/s41870-017-0071-2

    Google Scholar 

  4. Mehta R, Lobiyal D (2017) Utility-based performance analysis of cross-layer design in multi-flow ad-hoc networks. Int J Inf Process Springer 9(4):377–387

    Google Scholar 

  5. Aggarwal M, Nilay K, Yadav K (2017) Survey of named data networks: future of internet. Int J Inf Process Springer 9(2):197–207

    Google Scholar 

  6. Sun L, Li J, Chen Y, Zhu H (2005) Wireless sensor network. Tsinghua University Press, Beijing

    Google Scholar 

  7. Bao F, Chen I, Chang M, Cho J (2012) Hierarchical trust management for wireless sensor networks and its applications to trust-based routing and intrusion detection. IEEE Trans Netw Serv Manage 9(2):169–183

    Article  Google Scholar 

  8. Wood A, Stankovic J (2002) Denial of service in sensor networks. Comput IEEE 35(10):54–62

    Article  Google Scholar 

  9. Depren O, Topallar M, Anarim E, Ciliz M (2005) An intelligent intrusion detection system (IDS) for anomaly and misuse detection in computer networks. Expert Syst Appl Elsevier 29(4):713–722

    Article  Google Scholar 

  10. Azhagiri M, Rajesh A (2018) A novel approach to measure the quality of cluster and finding intrusions using intrusion unearthing and probability clomp algorithm. Int J Inf Process. https://doi.org/10.1007/s41870-018-0084-5

    Google Scholar 

  11. Muttoo S, Badhani S (2017) Android malware detection: state of the art. Int J Inf Process Springer 9(1):111–117

    Google Scholar 

  12. Feng R, Xu X, Zhou X, Wan J (2011) A trust evaluation algorithm for wireless sensor networks based on node behaviors and D-S evidence theory. Sensors 11(2):1345–1360

    Article  Google Scholar 

  13. Wu R, Deng X, Lu R, Shen X (2012) Trust-based anomaly detection in wireless sensor networks. In: 1st IEEE international conference on communications in China, IEEE, pp 203–207

  14. Atakli I, Hu H, Chen, Y, Ku W, Su Z (2008) Malicious node detection in wireless sensor networks using weighted trust evaluation. In: Proceedings of the 2008 spring simulation multi conference, ACM, pp 836–843

  15. Panda S, Jana P (2015) A multi-objective task scheduling algorithm for heterogeneous multi-cloud environment. In: International conference on electronic design, computer networks and automated verification, IEEE, pp 82–87

  16. Panda S, Jana P (2017) An efficient request-based virtual machine placement algorithm for cloud computing. In: 13th international conference on distributed computing and internet technology, Springer, pp 129–143

  17. Panda S, Jana P (2016) An efficient task consolidation algorithm for cloud computing. In: 12th international conference on distributed computing and internet technology, Springer, pp 61–74

  18. Panda S, Jana P (2017) SLA-based task scheduling algorithms for heterogeneous multi-cloud environment. J Supercomput Springer 73(6):2730–2762

    Article  Google Scholar 

  19. Wang J, Jiang S, Fapojuwo A (2017) A protocol layer trust-based intrusion detection scheme for wireless sensor networks. Sensors 17(6):12–27

    Google Scholar 

  20. Panda S, Jana P (2014) An efficient energy saving task consolidation algorithm for cloud computing. In: 3rd IEEE international conference on parallel, distributed and grid computing, IEEE, pp 262–267

  21. Panigrahi P, Panda S, Tripathy C (2015) Energy efficient task consolidation algorithms for cloud computing systems. Int J Inf Process 9(4):34–45

    Google Scholar 

  22. Rout J, Bhoi S, Panda S (2013) SFTP: a secure and fault-tolerant paradigm against blackhole attack in MANET. Int J Comput Appl 64(4):27–32

    Google Scholar 

  23. Rezazadeh J, Moradi M, Ismail A, Dutkiewicz E (2015) Impact of static trajectories on localization in wireless sensor networks. Wireless Netw Springer 21(3):809–827

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Umashankar Ghugar.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ghugar, U., Pradhan, J., Bhoi, S.K. et al. PL-IDS: physical layer trust based intrusion detection system for wireless sensor networks. Int. j. inf. tecnol. 10, 489–494 (2018). https://doi.org/10.1007/s41870-018-0147-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41870-018-0147-7

Keywords

Navigation