Randomized trial evaluates privacy-preserving data sharing in online social networks, suggesting improved privacy solutions.
Online social networks (OSNs) are immensely popular, but their centralized control of user data raises important privacy concerns. This paper presents Vis-à-Vis, a decentralized framework for OSNs based on the privacy-preserving notion of a Virtual Individual Server (VIS). A VIS is a personal virtual machine running in a paid compute utility. In Vis-à-Vis, a person stores her data on her own VIS, which arbitrates access to that data by others. VISs self-organize into overlay networks corresponding to social groups. This paper focuses on preserving the privacy of location information. Vis-à-Vis uses distributed location trees to provide efficient and scalable operations for sharing location information within social groups. We have evaluated our Vis-à-Vis prototype using hundreds of virtual machines running in the Amazon EC2 compute utility. Our results demonstrate that Vis-à-Vis represents an attractive complement to today's centralized OSNs.
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Shakimov et al. (2011) studied this question.
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