Incentive Mechanism for Cooperative Authentication: an Evolutionary Game Approach

Abstract In mobile opportunistic networks (MONs), cooperative authentication is an efficient way to filter false or misleading messages. However, due to privacy issues and concerns related to the consumption of resources, without adequate incentives, most mobile users (or nodes) with limited resources often act selfishly. These users are frequently uninterested to help others to authenticate such messages. In this study, a cooperative authentication model was formulated in the form of an evolutionary game. This model addresses the problems caused when cooperative nodes do not have all the information regarding other neighboring nodes, which makes them inadequately rational. Herein, the behavior dynamics and evolutionary stable strategy (ESS) of neighboring nodes were derived. We showed that the behavior dynamics converge to the ESS. This induces the neighboring nodes to independently decide whether to participate in authentication or not, without depending on information from other nodes (therefore, our approach can be implemented in the de-centralized manner). Further, a scheme to help the source node was also designed to determine an optimal budget. Experiments were conducted both on simulated as well as real datasets. The results demonstrate that our approach exhibits overwhelming advantages to incentivize selfish nodes in MONs to cooperate.