Defense against Spectrum Sensing Data Falsification Attacks Based on Adaptive Reputation Based Clustering

Abstract

The cognitive radio recommends collaborative spectrum sensing to avoid the unpredictability of personage spectrum sensing even as detecting primary user signals. A chance for attackers to take advantage of the decision making process by sending false reports. Security issues on the subject of dispersed node sensing in the 802.22 standard and talk about how attackers can modify or influence their sensing result independently or collaboratively. This problem is commonly recognized as spectrum sensing data falsification (SSDF) attack or Byzantine attack. To oppose the different attacking strategies, a reputation based clustering algorithm that does not necessitate preceding knowledge of attacker distribution or complete classification of malicious users. So provide an extensive probabilistic analysis of the performance of the algorithm. The performance of our algorithm in opposition to existing approaches across a wide range of attacking scenarios. Our planned algorithm displays a considerably reduced error rate in decision making in association to current methods. It also identifies a large portion of the attacking nodes and to the highest degree minimizes the false detection rate of truthful nodes.