Trust Establishment in Chaotic Cognitive Environment to Improve Attack Detection Accuracy Under Primary User Emulation

Abstract

In this paper, we propose a novel algorithm for primary user emulation attack detection and removal in cognitive radio networks, which are driven by chaotic tag-based sequencing for communication. Our proposed approach demonstrates the use of the look-up table-based challenge sequences which are monitored by the cognitive base station and act as the first line of defense against any primary user emulation attacker. This ensures that almost all of the attackers are suppressed, and for the remaining attackers if any, we use a tag-based chaotic communication system, wherein each of the requests from secondary users is sent like a chaotic noise sequence on the channel, and the receiving entity decodes this sequence in order to get the signal communicated by an authorized transmitter. If there is any communication by an attacker, then it is detected immediately, as none of the receiving entities can decode the signals sent by these unwanted attacker nodes. This ensures that our system guarantees greater than 99% detection and identification of attackers in primary user emulation attacks.