An Evolutionary Game Theoretical Framework for Decision Fusion in the Presence of Byzantines

It is an established fact that malicious users in networks are able to mislead other users since the presence of herd behaviors, which will further amplify the hazards of these malicious behavior. Due to the aforementioned scenarios in many practical applications, the study of decision fusion in the presence of such malicious users (often called Byzantines) is receiving increasing attentions. In this paper, we propose an evolutionary game theoretical model for decision fusion in the presence of Byzantines (EGT-DFB) to measure the hazard of Byzantines and to perform decision fusion. Specifically, we derive the evolution dynamics and the corresponding evolutionary stable states (ESS), which can be utilized to develop an optimum fusion strategy for the fusion center (FC) based on maximum a posterior probability criterion (MAP). Finally, simulation experiments are conducted to validate the performance of the proposed model and the effectiveness of decision fusion mechanism.