Mean Bid Trust Cross Layer Trust Evaluation Model for Cognitive Radio Networks

Abstract

Cognitive Radio Networks (CRNs) have come out as an encouraging next-generation network technology that addresses the issues related to scarce spectrum and enhanced utilization of spectrum in a significant manner. It is outlined to grant access for unlicensed users and use the highest accessible licensed bandwidth. Specifically Trust and Reputation Management models are more and more regarded for CRNs to secure them against the attacks posed by the secondary user that try to deprive others from utilizing the vacant space. The attacker or the malicious secondary user disturbs the security attributes by propagating attacks at different layers. In this paper, a method called, Mean Bid Trust and Multiple Nash Reputation (MBT-MNR) method is proposed to secure the CRN by detecting the attackers at two different layers, physical and network. First, trust is separately calculated for each CR user at two different layers, physical layer and network layer using trust parameters. Mean Bid Cross Layer Trust Evaluation model is applied to measure the trustworthiness of secondary user. Followed by which, the classification of malicious and normal user is made by applying the Multiple Nash Game Theory model. The performance of MBT-MNR method is evaluated based on detection time.

Keywords: Trust, Reputation, Mean Bid, Cross Layer attack, Cognitive Radio Networks, Multiple Nash Equilibrium