Trust based fusion over noisy channels through anomaly detection in cognitive radio networks

Byzantine attacks have been identified as one of the key vulnerabilities in cognitive radio networks, where malicious nodes advertise false spectrum occupancy data in a cooperative environment. In such cases, the resultant fused data is very different from the actual scenario. Thus, there is a need to identify the malicious nodes or at least find the trustworthiness of nodes such that the data sent by malicious nodes could be filtered out. The process is complicated by presence of noise in the channel which makes it harder to distinguish anomalies caused by malicious activity and those caused due to unreliable noisy channels.

This paper proposes a scheme for trust based fusion by monitoring anomalies in spectrum usage reports advertised over unreliable channels by secondary nodes which leads to evaluation of trust of a node by its neighbors. The calculated trust is then used to determine if a neighboring node's advertised data could be used for fusion or not. We provide a heuristic trust threshold for nodes to disregard malicious nodes while fusing the data, which holds good for any probability of attack. A trust coefficient is calculated based on interactions with peers in a distributed manner. Results show that even at higher probabilities of attack (0.8 and above), 95% of the nodes generate fused data with accuracy as high as 84%. We compare our results of trust based fusion with blind fusion scheme and observe improvement in accuracy of fusion from individual nodes' as well as overall network's perspective. We also analyze an alternative weighted trust fusion technique and evaluate its performance. We find that at lower probabilities of attack a malicious node's contribution to the overall gain in cooperation is more than the damage done. We observe that above a critical value for probability of attack of 0.40, the overall gain in cooperation is compromised if the malicious nodes are considered in fusion. We also discover that an honest node's benefit due to cooperation depends on its relative position with respect to the spatial orientation of malicious nodes.