Protecting Source Location Privacy in a Clustered Wireless Sensor Networks against Local Eavesdroppers

Recently, Wireless Sensor Networks (WSNs) have been extensively employed in several tactical applications out of which target detection, habit monitoring, and earthquake monitoring. The open characteristic nature of WSNs makes it vulnerable to be attacked by an eavesdropper who aims at disrupting the network operation or access confidential information. Consequently, ensuring the security and privacy in WSNs is considered an essential issue and definitely cannot be left without proper investigations. There are two types of threats that may occur for the WSNs privacy, that are, contextual and content privacy. Location privacy is considered an example of contextual privacy. In this paper, three source privacy protection schemes, which are based on clustering methodology, are proposed to protect contextual privacy. These schemes are dynamic shortest path (DSP) scheme, dynamic tree (DT) scheme, and hybrid scheme. Interestingly, a grid-based clustering technique is adopted to divide the network into several square clusters. Matlab simulations are used to evaluate the performance of the three proposed schemes in terms of latency, energy consumption, and safety period. The results undoubtedly confirm the effectiveness of the proposed schemes. Very high safety period is achieved and an adequate amount of energy is consumed. Furthermore, acceptable latency is achieved when compared to the shortest path scheme.