RSS Based Detection and Expulsion of Malicious Users from Cooperative Sensing in Cognitive Radios

In recent past there has been an increasing interest in wireless communication applications owing to its ease of use, cost effectiveness, maintainability and ease of deployment. Consequently, a number of wireless systems have been developed and deployed, thereby, leading to a belief that frequency spectrum is slowly running out of usable frequencies. Concept of Cognitive Radio (CR) has been proposed to overcome this issue of spectrum scarcity by making use of opportunistic spectrum access. Along with CRs, new types of security threats have evolved e. g. Primary User Emulation Attack (PUEA) and Spectrum Sensing Data Falsification (SSDF) attack. This paper introduces a simple yet efficient technique to counter the SSDF attack. Rigorous survey study shows that a handful of techniques are proposed to counter SSDF attack. The results show that the proposed techniques fail when malicious secondary users outnumber the genuine secondary users, which is a possible threat scenario in CR networks. We propose a technique that is independent of the number of malicious SUs in the network. It makes use of primary user's Received Signal Strength (RSS) at an SU to localize its position and compare this with that calculated using received signal strength of SU transmissions at data fusion center.