Skip to main content

Identifying and Eliminating the Misbehavior Nodes in the Wireless Sensor Network

  • Conference paper
  • First Online:
Soft Computing and Signal Processing (ICSCSP 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1413))

Included in the following conference series:

Abstract

In recent years, advanced research in wireless sensor networks (WSN) has become a trending and emerging technology. Sensors can be used to monitor physical and environmental conditions, and they are also used in the manufacturing industry. Battery life and security issues are the two most significant problems and challenges in wireless sensor networks. Many algorithms have been developed to implement the above issues in many other situations, but both issues are not fully resolved due to a variety of factors, such as duplication of data that is not filtered, wasting battery power, and bandwidth. Some nodes in the network become selfish, unable to forward packets to neighboring nodes. These nodes cause network misbehavior, rendering the network partially inactive. Our proposed method entails removing misbehaving nodes from the network as well as checking for message duplication in the network before sending data, and our algorithm satisfies the aforementioned requirements.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. A. Kathirvel, R. Srinivasan, ETUS: enhanced triple umpiring system for security and robustness of wireless mobile ad hoc networks. Int. J. Commun. Netw. Distrib. Syst. 7(1/2), 153–187 (2017)

    Google Scholar 

  2. A. Kathirvel, R. Srinivasan, ETUS: an enhanced triple umpiring system for security and performance improvement of mobile ad hoc networks. Int. J. Netw. Manag. 21(5), 341–359 (2018)

    Article  Google Scholar 

  3. S.E. Deering, Multicast routing in internetworks and extended LANs, in Proceedings of the ACM SIGCOMM Symposium on Communication Architecture and Protocols, Aug 2019, pp. 55–64

    Google Scholar 

  4. T. Ballardie, J. Crowcroft, Multicast-specific security threats and counter-measures, in Proceedings of the Second Annual Network and Distributed System Security Symposium (NDSS ‘95), Feb 2019, pp. 2–16

    Google Scholar 

  5. Y. Zhou, X. Zhu, Y. Fang, MABS: multicast authentication based on batch signature. IEEE Trans. Mob. Comput. 9(7), 982–993 (2018)

    Article  Google Scholar 

  6. J. Jeong, Y. Park, Y. Cho, Efficient DoS resistant multicast authentication schemes, in Proceedings of the International Conference on Computational Science and Its Applications, 2010, pp. 353–362

    Google Scholar 

  7. A. Perrig, R. Canetti, J.D. Tygar, D. Song, Efficient authentication and signing of multicast streams over lossy channels, in Proceedings of the IEEE Symposium on Security and Privacy (SP ‘00), May 2000, pp. 56–75

    Google Scholar 

  8. S. Miner, J. Staddon, Graph-based authentication of digital streams, in Proceedings of the IEEE Symposium on Security and Privacy (SP ‘01), May 2001, pp. 232–246

    Google Scholar 

  9. N. Koblitz, Elliptic curve cryptosystems. Math. Comput. 48, 203–209 (1987)

    Article  MathSciNet  Google Scholar 

  10. M. Kefayati, H.R. Rabiee, S.G. Miremadi, A. Khonsari, Misbehavior resilient multi-path data transmission in mobile ad-hoc networks, in Proceedings of the fourth ACM Workshop Security of Ad Hoc and Sensor Networks (SASN ’06), 2006

    Google Scholar 

  11. R. Mavropodi, P. Kotzanikolaou, C. Douligeris, SecMR—a secure multipath routing protocol for ad hoc networks. Ad Hoc Netw. 5(1), 87–99 (2007)

    Article  Google Scholar 

  12. B. Xiao, B. Yu, C. Gao, Chemas: identify suspect nodes in selective forwarding attacks. J. Parallel Distrib. Comput. 67(11) (2007)

    Google Scholar 

  13. X. Zhang, A. Jain, A. Perrig, Packet-dropping adversary identification for data plane security, in Proceedings of the 2008 ACM CoNEXT Conference (CoNEXT ‘08), 2008

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Navaneethan Selvaraj .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Selvaraj, N., Madhan, E.S., Kathirvel, A. (2022). Identifying and Eliminating the Misbehavior Nodes in the Wireless Sensor Network. In: Reddy, V.S., Prasad, V.K., Wang, J., Reddy, K. (eds) Soft Computing and Signal Processing. ICSCSP 2021. Advances in Intelligent Systems and Computing, vol 1413. Springer, Singapore. https://doi.org/10.1007/978-981-16-7088-6_36

Download citation

Publish with us

Policies and ethics