An Adaptive Neural Network for Primary User Emulation Attacks in Cognitive Radio Network
Shilpa Biradar, Kishan Pal Singh · 2023
The shortage of spectrum during peak hours slows up the speed of the network due to the increasing number of gadgets where, the licensed primary users (PUs), as well as the unlicensed secondary users (SUs) in CRN employ the spectrum resources together by evading intervention from SUs. Even though, the process of spectrum sensing is regularly distracted by a safety problem termed the Primary User Emulation Attack (PUEA). A model of an adaptive neural network (ANN) is developed for PUEA in CRN to recognize the secondary users when acting as the primary user and detect the attack adaptively without intruding on the network functioning. The proposed PUED model detects the attack that arises in the network and provides authentication to the unlicensed user that utilizes the spectrum that is not used. The proposed method’s results state that the delay is decreased and the throughput of the proposed method increased to 499.494kbps when compared to the existing methods.