WITHDRAWN: A Dynamic and adaptive learning mechanism to reduce cross layer attacks in cogntive networks

Abstract

Malicious users can make use of vulnerabilities in Cognitive networks or in any kind of wireless networks and cause Serious degradation of performance, throughput by various denial of service (DoS) attacks. In cognitive radio networks, cognitive radios (CRs) expend a significant amount of time to find idle channels for data diffusion. In addition, CRs also require supplementary defense mechanism to avoid wicked attacks. Various MAC Protocols for CR’s can be useful for idle channels identification. However, such exterior detection mechanism uses extra power that makes them unsuitable for energy guarded applications. As a Result, a Dynamic and Adaptive learning mechanism which can resist the attacks and capable of sending data to destination is simulated here. Dynamic and Adaptive learning mechanism is proposed that shows protection to DOS attacks without any external detection mechanism. If this Dynamic and Adaptive learning mechanism architecture is utilized in cognitive radio networks or any wired networks we can save energy and reduce any external DOS attacks. Dynamic and adaptive based learning mechanism shows and improvement of 6.3%, 12.5% and 21% improvement in throughput, Sensing Delay and energy Consumption Respectively when compared to latest MAC Protocols for Cognitive Radio Networks.