SBE TWC: Small: Collaborative: Privacy Protection in Social Networks: Bridging the Gap Between User Perception and Privacy Enforcement

在线社交网络，如Facebook、Twitter和b谷歌+，已经变得非常流行。它们极大地改变了我们分享信息和社交的行为，尤其是在年轻一代中。然而，这种网络社交网络的极度普及也成为一把双刃剑——在促进网络社交的同时，这些系统也引发了隐私问题。为了在不影响社交功能的情况下保护用户隐私，该项目阐明了一个统一的框架，弥合了以人为本和以技术为中心的观点之间的差距。具体而言，本项目正在开发以下方法：(1)检测用户信息共享期望与实际信息披露之间的差异；(2)设计一个以用户为中心且计算效率高的社交网络用户隐私形式化模型；(3)开发一种机制来有效地执行所提出模型中的隐私策略。潜在的长期社会效益是显著的，因为这种意识可能会逐渐改变人们的隐私观念，并影响他们在以隐私为中心的情况下的行为。该项目提出了“社交圈”概念，在限制访问和限制控制框架下模拟社交网络访问。正在发展各种方法，以便从社会网络内各种类型的现有信息推导出社交圈；这些参数用于确定适当的访问控制设置。该项目正在评估在这种情况下的信息流和泄漏风险，包括系统异质性引起的问题。除了对各种对手模型的潜在信息流进行理论分析外，该项目还进行了用户研究，以确定这种方法是否减少了感知到的隐私和实际隐私之间的差距。

Online social networks, such as Facebook, Twitter, and Google+, have become extremely popular. They have significantly changed our behaviors for sharing information and socializing, especially among the younger generation. However, the extreme popularity of such online social networks has become a double-edged sword -- while promoting online socialization, these systems also raise privacy issues. To protect user privacy without compromising socialization functions, this project articulates a unifying framework that bridges the gap between the human-oriented and technology-centered perspectives. In particular, this project is developing methods to (1) detect the discrepancies between users' information sharing expectations and actual information disclosure; (2) design a user-centered yet computationally-efficient formal model of user privacy in social networks; and (3) develop a mechanism to effectively enforce privacy policies in the proposed model. The potential long-term social benefits are significant, since such awareness may gradually change people's privacy perceptions and affect their behavior in privacy-centric scenarios. This project develops a concept of "Social Circles" to model social network access within a Restricted Access and Limited Control framework. Methods are being developed to derive social circles from a variety of types of existing information within the social network; these are used to determine appropriate access control settings. The project is assessing information flow and risk of leakage given such settings, including the issues raised by heterogeneity of systems. In addition to theoretical analysis of potential information flows with respect to a variety of adversary models, the project is conducting user studies to determine if this approach reduces the gap between perceived and actual privacy.