TWC: Small: Virtual Private Social Networks

社交网络服务已经从一站式网站转变为与第三方网站、应用程序甚至操作系统深度集成的社交平台。作为突出的例子，Facebook的Like和Google的+1按钮等社交插件使网站能够提供个性化的内容，并允许他们的访问者无缝地与他们的社交圈分享和互动，而Facebook和Twitter的支持已经集成到iOS 6中。这些社交功能为用户和内容提供商提供了多方面的好处，并推动它们在网络和移动应用生态系统中得到广泛采用。然而，这种日益增长的集成引起了人们对这些社交功能对用户隐私的影响的担忧，因为它们使社交网络服务能够跟踪越来越多的成员活动，包括他们的浏览历史、位置和通信。该项目中的研究试图通过探索一种保护隐私的虚拟私人社交网络的新设计来解决这些隐私问题，该设计满足了两个看似相互矛盾的要求：它通过最大限度地减少用户识别信息传输到社交网络平台来保护用户隐私，同时通过提供相同的个性化内容来保留所有现有功能。这种方法的主要见解是通过将潜在敏感社交信息的检索与使用该信息的个性化内容的呈现分离，将内容个性化从服务器端流程转移到客户端流程。PI正在开发一种个性化的“信息覆盖”，它独立于第三方访问从用户的社交圈预取信息，并在用户的设备上保持这些信息的一致性。这项研究的结果预计将显著改善社交网络服务成员的隐私，而不会降低他们已经习惯的当前个性化体验。

Social networking services have been transformed from one-stop websites, to social interaction platforms deeply integrated with third-party websites, applications, and even operating systems. As prominent examples, social plugins such as Facebook's Like and Google's +1 buttons enable websites to offer personalized content and allow their visitors to seamlessly share and interact with their social circles, while Facebook and Twitter support is already integrated in iOS 6. These social features offer multifaceted benefits to both users and content providers, and have driven their widespread adoption across the web and the mobile application ecosystem. However, this increasing integration has raised concerns about the implications of these social features to user privacy, as they enable social networking services to track a growing part of their members' activity, including their browsing histories, locations, and communications.The research in this project seeks to address these privacy concerns by exploring a novel design for privacy-preserving virtual private social networks, which fulfills two seemingly contradicting requirements: it protects user privacy by minimizing the transmission of user-identifying information to the social networking platform, while preserving all existing functionality by delivering the same personalized content. The main insight of this approach is to shift content personalization from a server-side to a client-side process, by decoupling the retrieval of potentially sensitive social information from the presentation of personalized content that uses that information. The PIs are developing a personalized "information overlay" that prefetches information from a user's social circle independently of third-party accesses, and keeps this information consistent across the user's devices. The outcomes of this research effort are expected to significantly improve the privacy of members of social networking services, without degrading the current personalization experience to which they have grown accustomed.