A Multi-factor Trust Management Scheme for Secure Spectrum Sensing in Cognitive Radio Networks

Abstract

Cognitive radio (CR) is an emerging technology for efficient utilization of the limited and scarce radio spectrum resources. Spectrum sensing is a key task in CR system for detecting the unused radio spectrum or spectrum holes by the primary users. In this regard, collaborative spectrum sensing (CSS) has shown to as an efficient way to improve such spectrum holes detection in cognitive radio network (CRN). However, this cooperative nature makes it vulnerable to many types of security attacks. In this paper, we focus one of these potential CRN specific security attack called spectrum sensing data falsification attack or Byzantine attack. In which the malicious internal member of the network, reports false sensing results with a aim to increase the sensing errors. In order to ensure the security requirements of CRN, we proposed a novel trust management mechanism that evaluates the trustworthiness of each node participating in the CSS scheme called sensing reputation (SR). To reflect the complexity, the SR calculation involves multiple decision factors like history based trust factor, active factor, incentive factor and consistency factor. Based on this SR value, the suspicious users are identified and the malicious users are filtered out from the decision making process of the CSS scheme. We further introduce the concept of sensing reputation chain to record and track the future behavior of the identified suspicious users. Theoretical analysis and simulation results demonstrate the effectiveness of our proposed malicious user detection technique with a higher accuracy and lower false alarm rate.