The impact of interactive dependence on privacy protection behavior based on evolutionary game

With the rapid development of social networks, privacy protection has become a hot issue in the field of information security. Here we introduce the framework of evolutionary game theory to explore the issue of privacy protection in social networks. Since reciprocity is widely present in social activities, we introduce the heterogeneous interaction mode, in which players can adopt different strategies for different opponents. In addition, the parameter u is introduced to measure the player's dependence on the opponent who interacts directly with the central individual during the update strategy phase. Here, we explore the impact of heterogeneous interaction dependency strength on privacy protection. A series of computer simulation results suggest that heterogeneous decision behavior can promote privacy protection, and there exists an optimal dependence strength interval for the group to achieve a higher level of privacy protection. Certainly, larger reciprocity strength and smaller cost can significantly increase the privacy protection behavior. Our research work is of great significance in solving the long-term safe and effective development of social networks.