Community-Structured Evolutionary Game for Privacy Protection in Social Networks
Community-Structured Evolutionary Game for Privacy Protection in Social Networks
复制标题
用于社交网络隐私保护的社区结构演化博弈
DOI：
10.1109/tifs.2017.2758756
复制
发表时间：
2018-03
影响因子：
6.8
通讯作者：
Jun Du;Chunxiao Jiang;Kwang-Cheng Chen;Yong Ren;H. Poor
中科院分区：
文献类型：
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作者：
Jun Du;Chunxiao Jiang;Kwang-Cheng Chen;Yong Ren;H. Poor
社交网络吸引了数十亿用户，并支持广泛的兴趣和做法。社交网络的用户可以根据职业、生活地点和个人兴趣通过不同的社区彼此连接。随着社会网络应用的多样化发展，相关技术越来越受到学术研究者和实践工程师的关注。由于社交网络平台上的每个用户通常存储和共享大量个人数据，因此这种用户相关信息的隐私引起了严重的关注。大多数关于隐私保护的研究依赖于特定的信息安全技术，如匿名化或访问控制。然而，隐私的保护在很大程度上取决于社交网络的激励机制，如用户对安全执行的心理决定和社会经济考虑。例如，影响其他人的行为的愿望可能会改变用户对安全设置的选择。在本文中，建立了一个博弈论的框架来模拟用户的互动，影响用户的决策，是否进行隐私保护或不。为了模拟用户社区的关系，社区结构的进化动力学，其中用户的交互只能发生在那些用户之间谁拥有至少一个共同的社区。然后基于社区结构演化博弈理论框架，分析了用户采取或不采取特定隐私保护策略的动态变化。实验表明，该框架能够有效地对用户关系和隐私保护行为进行建模。此外，研究结果还可以帮助社会网络管理者设计适当的安全服务和支付机制，鼓励用户采取隐私保护措施，从而促进隐私行为在整个网络中的传播。
Social networks have attracted billions of users and supported a wide range of interests and practices. Users of social networks can be connected with each other by different communities according to professions, living locations, and personal interests. With the development of diverse social network applications, academic researchers, and practicing engineers pay increasing attention to the related technology. As each user on the social network platforms typically stores and shares a large amount of personal data, the privacy of such user-related information raises serious concerns. Most research on privacy protection relies on specific information security techniques such as anonymization or access control. However, the protection of privacy depends heavily on the incentive mechanisms of social networks, like users’ psychological decisions on security execution and socio-economic considerations. For example, the desire to influence the behaviors of other people may change a user’s choice of security setting. In this paper, a game theoretic framework is established to model users’ interactions that influence users’ decisions as to whether to undertake privacy protection or not. To model the relationship of user communities, community-structured evolutionary dynamics are introduced, in which interactions of users can only happen among those users who have at least one community in common. Then the dynamics of the users’ strategies to take a specific privacy protection or not is analyzed based on the proposed community structured evolutionary game theoretic framework. Experiments show that the proposed framework is effective in modeling the users’ relationships and privacy protection behaviors. Moreover, results can also help social network managers to design appropriate security service and payment mechanisms to encourage their users to take the privacy protection, which can promote the spreading of privacy behavior throughout the network.