A simple and highly effective SSDF attacks mitigation method

Abstract

This paper presents a method to alleviate spectrum sensing data falsification (SSDF) attacks in cognitive radio networks. Spectrum sensing data falsification attacks have been identified as an important unsolved security issue in cognitive radio networks. In essence, SSDF attackers target co-operated spectrum sensing networks. Malicious users send out falsified information about spectrum sensing results (whether a channel is idle or not) in order to deceive legitimate secondary users. To mitigate against SSDF attacks, we introduce a reputation based scheme. Our method is a distributed scheme, in which each secondary user is responsible for gathering and processing data. A distributed scheme is used to mitigate the effects that shadowing and noise have on local observations. Using a distributed scheme allows secondary users to receive additional information from neighboring secondary users, enabling higher accuracy of results. We base our method on a modified belief propagation algorithm that uses reputation as a weighted scalar. Within the reputation scheme, honest users are rewarded with an increase in their reputation. Dishonest users are punished with a decrease in their reputation. Users with a high reputation have a higher influence on the final decision on whether the channel is in use or not. The method presented in this paper is a simple, highly effective way to mitigate spectrum sensing data falsification attacks. It is able to converge quickly and offers high accuracy identification and mitigation of a malicious node.