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Intrusion Detection Based on k-Coverage in Mobile Sensor Networks with Empowered Intruders

Research output: Contribution to journalArticle

  • Haiping Huang
  • Tianhe Gong
  • Rong Zhang
  • Lie Liang Yang
  • Jiancong Zhang
  • Fu Xiao
Original languageEnglish
Article number8477168
Pages (from-to)12109-12123
Number of pages15
JournalIEEE Transactions on Vehicular Technology
Volume67
Issue number12
Early online date1 Oct 2018
DOIs
DateAccepted/In press - 5 Sep 2018
DateE-pub ahead of print - 1 Oct 2018
DatePublished (current) - Dec 2018

Abstract

Intrusion detection is one of the important applications of wireless sensor networks (WSNs). Prior research indicated that the barrier coverage method combined with mobile sensor networks (MSNs) can enhance the effectiveness of intrusion detection by mitigating coverage holes commonly appearing in stationary WSNs. However, the trajectories of moving sensors and moving intruders have not been investigated thoroughly, whereas the impact between two adjacent moving sensors and between a moving sensor and a moving intruder are still under-determined. In order to address these open problems, in this paper, we firstly discuss the virtual potential field between sensors as well as between sensors and intruders. We then propose to formulate the mobility pattern of sensor node using elastic collision model and that of intruder using point charge model. The point charge model describes an hitherto unexplored mobility pattern of empowered intruders, which are capable of acting upon the virtual repulsive forces from sensors in order to hide them away from being detected. With the aid of the two models developed, analytical expressions and simulation results demonstrate that our proposed design achieves a higher $k$-barrier coverage probability in intrusion detection compared to that of the conventional designs. It is also worth mentioning that these improvements are achieved with shorter average displacement distance and under much more challenging MSNs settings.

    Research areas

  • empowered intruders, intrusion detection, k-barrier coverage, Mobile sensor networks

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