Detection of Attackers in Cognitive Radio Network Using Optimized Neural Networks

Cognitive radio network (CRN) is a growing technology targeting more resourcefully exploiting the available spectrum for opportunistic usage. By concept of cognitive radio, wastage reduced about 30% worldwide. The key operation CRN sensing. sensing results are directly proportional to performance network. In CRN, final result decided by combing local results. presence or participation attackers in leads false decisions and will be degraded. this work, an optimized artificial neural (ANN) based aggressor classification algorithm proposed. ANN improved using Immune plasma optimization (IPO) which inspired human immune system response COVID-19 disease. Results indicate that proposed IP produces better terms attacker detection accuracy, energy, packet delivery ratio delay show method has 32% accuracy rate improvement’s, 16% energy savings, 40% improvements overall reductions than existing methods.