Trust Aware Scheme based Malicious Nodes Detection under Cooperative Spectrum Sensing for Cognitive Radio Networks

Abstract

Emerging of Cognitive Radio (CR) technology has provided optimistic solution for the dearth of spectrum by improving the spectrum utilization. The opportunistic use of the spectrum is enabled by spectrum sensing which is one of the key functionality of CR systems. To perform the interference free transmission in a cognitive radio networks, an important part for unlicensed user is to identify a licensed user with the help of spectrum sensing. Recently, the Cooperative Spectrum Sensing has been widely used in the literature where various scattered unlicensed users collaborate with each other to make the final sensing decision. This overcome the hidden terminal problem and also improve the overall reliability of the decisions made about the presence or absence of a licensed user. Each unlicensed user send the sensing results to the base station for final decision. However there exist some nodes which do not provide the correct sensing results to maximize their own profit which can highly degrade the CR network functionality. In this paper, a trust aware model is proposed for detection of misbehaving nodes such that their sensing reports can be filter out from the final result. The performance evaluation of the proposed scheme is done by checking its robustness and efficiency against various possible attacks.

AI‐enabled trust‐based routing protocol for social opportunistic IoT networks

“…Malicious nodes bloat their competency to meet with the destination node to intercept the message coming from sender nodes, which results in a degradation in network performance 15,16 . As a result, a trustworthy and secure message transmission protocol is a challenge that checks on the node's behavior for assisting other nodes in forwarding messages and does not support any attack, deception, and camouflage 17,18 . Moreover, social OppIoT supports a social Oppnets phenomenon in which most nodes are interested in cooperating with other nodes who frequently meet at an ordinary time, space and have familiar neighbors' history and behavior.…”

“…15,16 As a result, a trustworthy and secure message transmission protocol is a challenge that checks on the node's behavior for assisting other nodes in forwarding messages and does not support any attack, deception, and camouflage. 17,18 Moreover, social OppIoT supports a social Oppnets phenomenon in which most nodes are interested in cooperating with other nodes who frequently meet at an ordinary time, space and have familiar neighbors' history and behavior. Therefore trust measurement of the nodes based on multiple factors of collaboration needs to be solved urgently.…”