A Reverse Gaussian deployment strategy for intrusion detection in wireless sensor networks

Intrusion detection is one of many typical applications for wireless sensor networks (WSNs). A WSN for intrusion detection application is capable of detecting any physical existence of external intruder invading an area under protection and alert the system for appropriate actions. Traditional deployment schemes for intrusion detection usually consider detection probability of having separate facilities within the monitored area. In this work, we assume that the scenario includes multiple facilities. A Reverse Gaussian distribution is derived from two dimensional Gaussian distribution and sensors are deployed following a Reverse Gaussian distribution. By placing a larger number of sensor nodes at the border, the detection probability is enhanced. As intrusion attacks start from border area, Reverse Gaussian deployment scheme can provide a better security performance with the same amount of investment as compared to traditional deployment schemes, and is validated by extensive simulation results.