Visible to the public SBE TWC: Small: Collaborative: Privacy Protection in Social Networks: Bridging the Gap Between User Perception and Privacy EnforcementConflict Detection Enabled

Project Details

Lead PI

Performance Period

Oct 01, 2014 - Sep 30, 2018

Institution(s)

University of Kansas Center for Research Inc

Award Number


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.