Joint Malicious Source Detection and Target Localization using Compartmental Model in Cluster-based Networks

The communication between the transmitter and the receiver is generally affected by malfunctioning sources, sensing of abnormal phenomena (outlier), non-line-of-sight (NLOS) communication, multipath fading or any other external attack. In this paper, joint malicious source detection and robust target localization method using the compartmental model is presented. Compartmental model is the sum of two exponentials which describe the variation of received signal strength with transmitter-receiver distance. Additionally, a data aggregation unaware clustering technique based on first and second order approximations of the compartmental model is presented. The effectiveness of the proposed method is verified using real field deployment in an indoor scenario.