Multi-Party Privacy Conflict Management in Online Social Networks: A Network Game Perspective

In this work, we consider the multi-party privacy conflict (MPC) in an online social network (OSN). As many data items uploaded to the OSN are "co-owned" by multiple users with different privacy concerns, some personal information of OSN users may be disclosed by others unintentionally. On the contrary with existing mainstream OSN platforms allowing only the very user uploading the data to set the privacy level, in this article we take a fine-grained approach to resolve MPC, in which all co-owners independently determine whether to share their personal content within the data on OSN. Interacted with its peers, the opinion of a co-owner, however, might be influenced by and consequently influence the decision of its peers. To this end, each co-owner, as an individual decision maker, strikes a tradeoff between its internal privacy preference and the external social influence from its neighbors in a OSN. Specifically, we formulate the interaction among co-owners as a multi-player non-cooperative game with a network structure representing their social relations. For the proposed network game, we establish the existence of multiple (pure-strategy) equilibria, and characterize them accordingly. The convergence of interaction is also investigated when synchronous and asynchronous best-response updates are used, respectively. We note that when the action set for the players is discrete, the game exhibits non-linear dynamics, making it challenging to analyze the convergence behavior. We prove that synchronous update may lead to either an equilibrium or a strategy cycle, and the asynchronous update always leads to an equilibrium. Building upon this analysis, we advocate a practical implementation of the proposed MPC management, which balances the automation of the management and intervention of users. Moreover, we take one step further to develop approaches aiming to reach a "stronger agreement" among the players for the sake of benefits of uploader and OSN provider. Numerical examples are also provided to corroborate the analytical results.