Security in Cognitive Radio Network: Defense against Primary User Emulation attacks using Genetic Artificial Bee Colony (GABC) algorithm

摘要

Due to the exponential increase in the number of wireless devices and in data rates demands, the shortage of the free frequency spectrum resources becomes a critical problem. Cognitive Radio Network (CRN) is considered as an emerging technology that eases off the problem of spectrum shortage by optimizing the usage of the available spectrum through giving the unlicensed Secondary Users (SU) the opportunity to exploit the spectrum without causing any interference with the Primary Users' (PU) usage. Securing the CRN is a crucial problem that must be addressed. Primary User Emulation (PUE) attacks are one of the main threats in deploying CRN, where the Malicious Users mimic the PU signal to confuse the other SUs and corrupt the spectrum sensing process. Many efforts had been made for securing the spectrum sensing process. In this paper, a hybrid Genetic Artificial Bee Colony (GABC) algorithm is proposed to optimize the spectrum utilization by detecting the PUE attacks and enhancing the probability of detection. GABC integrates the Genetic operators with ABC algorithm to reach the balance between exploitation and exploration to find the optimal solution. The simulations results show promising performance of GABC in optimizing spectrum sensing, when compared with recent detection algorithms.