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Probabilistic Intrusion Detection in Randomly Deployed Wireless Sensor Networks

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Abstract

Wireless sensor networks (WSNs) are commonly used in surveillance to sense the event of interest in the monitoring field and report it to the sink in a timely manner. In Area coverage, network monitors the Area of interest and recognizes any intruder attempting to cross the monitoring Area. In this paper, we have analyzed the intruder detection probability with respect to network parameters such as sensing radius, node density. We also investigated the detection probability related to speed of intruder, availability of sensor nodes along with the time frame required to identify the intruder. In addition, we also discussed the k-detection probability to make the system more reliable. Furthermore in this paper we have also developed the analytical framework for the expected hop count in multi-hop WSN .

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References

  1. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38, 393–422.

    Article  Google Scholar 

  2. Wang, Y., Wang, X., Xie, B., Wang, D., & Agrawal, D. P. (2008). Intrusion detection in homogeneous and heterogeneous wireless sensor networks. IEEE Transactions on Mobile Computing, 7(6), 698–711.

    Article  Google Scholar 

  3. Harada, J., Shioda, S., & Saito, H. (2008). Path coverage properties of randomly deployed sensors with finite data-transmission ranges. Computer Networks, 53, 1014–1026.

    Article  Google Scholar 

  4. Chen, A., Lai, T. H., & Xuan, D. (2008). Measuring and guaranteeing quality of barrier-coverage in wireless sensor networks. In Proceedings of the 9th ACM international symposium on mobile ad hoc networking and computing, pp. 421–430.

  5. Kumar, S., Lai, T. H., & Arora, A. (2005). Barrier coverage with wireless sensors. In Proceedings of the 11th annual international conference on Mobile computing and networking, pp. 284–298.

  6. Li, L., Zhang, B., & Zheng, J. (2013). A study on one-dimensional k-coverage problem in wireless sensor networks. Wireless Communications and Mobile Computing, 13, 1–11.

    Article  Google Scholar 

  7. Wang, Y., & Lun, Z. (2011). Intrusion detection in a K-Gaussian distributed wireless sensor network. Journal of Parallel and Distributed Computing, 71, 1598–1607.

    Article  MATH  Google Scholar 

  8. Xiao, Y., Chen, H., Wu, K., Sun, B., Zhang, Y., Sun, X., et al. (2010). Coverage and detection of a randomized scheduling algorithm in wireless sensor networks. IEEE Transactions on Computers, 59, 507–521.

    Article  MathSciNet  Google Scholar 

  9. Xiao, Y., Zhang, Y., Peng, M., Chen, H., Du, X., Sun, B., et al. (2009). Two and three-dimensional intrusion object detection under randomized scheduling algorithms in sensor networks. Computer Networks, 53, 2458–2475.

    Article  MATH  Google Scholar 

  10. Mostafaei, H., & Meybodi, M. R. (2013). Maximizing lifetime of target coverage in wireless sensor networks using learning automata. Wireless Personal Communications, 71, 1461–1477.

    Article  Google Scholar 

  11. Kumar, S., Lai, T. H., Andbalogh, J. (2004). On k-coverage in a mostly sleeping sensor network. InProceedings of MobiCom’04, pp. 144–158.

  12. Harb, S. M., & McNair, J. (2008). Analytical study of the expected number of hops in wireless ad hoc network. WASA 2008, LNCS 5258, pp. 63–71.

  13. Bettstetter, C. (2002). On the minimum node degree and connectivity of a wireless multihop network. In Proceedings of MOBIHOC’02, pp. 80–91.

  14. Ewens, W., & Grant, G. (2004). tatistical methods in bioinformatics: An introduction. Berlin: Springer.

    Google Scholar 

Download references

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Authors and Affiliations

  1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Anil Kumar Sagar & D. K. Lobiyal

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  1. Anil Kumar Sagar
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  2. D. K. Lobiyal
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Correspondence to Anil Kumar Sagar.

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Sagar, A.K., Lobiyal, D.K. Probabilistic Intrusion Detection in Randomly Deployed Wireless Sensor Networks. Wireless Pers Commun 84, 1017–1037 (2015). https://doi.org/10.1007/s11277-015-2673-y

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  • DOI: https://doi.org/10.1007/s11277-015-2673-y

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