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.

中文翻译：

---

在线社交网络中的多方隐私冲突管理：网络游戏视角


在这项工作中，我们考虑在线社交网络（OSN）中的多方隐私冲突（MPC）。由于上传到 OSN 的许多数据项由具有不同隐私关注的多个用户“共同拥有”，因此 OSN 用户的某些个人信息可能会被其他人无意中泄露。与现有的主流OSN平台只允许上传数据的用户设置隐私级别相反，在本文中我们采用细粒度的方法来解决MPC，其中所有共同所有者独立决定是否共享他们的个人内容OSN 上的数据中。然而，在与同行互动时，共同所有者的意见可能会受到同行的影响，从而影响其决策。为此，每个共同所有者作为个人决策者，在其内部隐私偏好和 OSN 中邻居的外部社会影响之间进行权衡。具体来说，我们将共同所有者之间的互动表述为多人非合作博弈，并采用代表其社会关系的网络结构。对于所提出的网络游戏，我们建立了多重（纯策略）均衡的存在，并相应地描述了它们的特征。当分别使用同步和异步最佳响应更新时，还研究了交互的收敛性。我们注意到，当玩家的动作集是离散的时，游戏就会表现出非线性动态，这使得分析收敛行为变得具有挑战性。我们证明同步更新可能导致均衡或策略循环，而异步更新总是导致均衡。 在此分析的基础上，我们主张实际实施所提出的 MPC 管理，以平衡管理的自动化和用户的干预。此外，为了上传者和 OSN 提供商的利益，我们进一步制定了旨在在玩家之间达成“更强有力的协议”的方法。还提供了数值例子来证实分析结果。