Applying general sensing mode to intrusion detection in wireless sensor networks

Authors:
Tao Liu;Zhishu Li;Feng Yin;Jun Yang
Affiliations:
College of Computer Science, Sichuan University, Chengdu, China and College of Computer Science and Technology, Southwest University for Nationalities, Chengdu, China;College of Computer Science, Sichuan University, Chengdu, China;College of Computer Science and Technology, Southwest University for Nationalities, Chengdu, China;College of Computer Science and Technology, Southwest University for Nationalities, Chengdu, China
Venue:
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Year:
2009

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Abstract

Intrusion detection is defined as a mechanism for a WSN to detect the existence of inappropriate or anomalous moving attackers via the sensors. All previous studies on intrusion detection are primarily based on the Boolean sensing model. But experiments and experience suggest the general sensing model is more reasonable for radio, acoustic and seismic signals than the Boolean sensing model. In this paper, we apply general sensing model to calculate the sensing signal, and integrator model to identify a moving intruder. Furthermore, we provide theoretical formulations for the intrusion detection probability in WSNs that follow uniform and Gaussian distributions. Our simulation results indicate the correctness of our analytical models.