To attack or not to: an evolutionary game model to study the dynamics of selfish PUEA attackers in cognitive radio networks

摘要

The current paradigm shift towards heterogeneous wireless networks is being spearheaded by 5G technology for which cognitive radio networks (CRNs) have evolved as a promising enabling technology. CRNs are susceptible to primary user emulation attacks (PUEAs). This current work is an attempt to use evolutionary game theory (EGT) to study the dynamics of selfish SUs (PUEA) and normal SUs in a CRN. The game formulation and the analysis thereof, are conclusive of the fact that in a CRN running an intrusion detection system (IDS) with a very high rate of detection of the attackers, the winning strategy turns out to be the normal strategy. However, if the IDS's detection rate is kept relatively high (60%), the ultimate winning strategy depends on the percentage of the initial population, where the more populous one continues to influence others to convert, and finally leading to become the dominant strategy.