III: Small: Collaborative Research: Privacy-Aware Collaborative Data Sharing in Human-Centered Social Networks

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With the help of Online Social Networks (OSNs), people share personal and public information and make social connections with friends, coworkers, colleagues, family and even with strangers. As a result, OSNs store a huge amount of sensitive information about users and their interactions. To protect such information, privacy control has been treated as a central feature of OSNs. Although OSNs currently provide some privacy control mechanisms allowing users to regulate access to information they share, users, unfortunately, have no control over data others share. For instance, if a user posts a comment in a friend's space, s/he cannot specify which users can view the comment. Similarly, when a user uploads a photo and tags friends who appear in the photo, the tagged friends cannot restrict who can see this photo. Since multiple associated users may have different privacy concerns over the shared data, privacy conflicts occur and the lack of collaborative privacy control increases the potential risk of leaking sensitive information by friends to the public. To address such a critical issue, it is essential to accommodate diverse privacy control requirements coming from multiple associated users for collaboratively managing the shared data in OSNs. The new techniques developed in this project will substantially enhance the state-of-the-art in privacy-aware data sharing in OSNs and will have implications for the design of future collaborative sharing systems in OSNs. Moreover, since privacy practices in many other collaborative environments, such as electronic health records and financial data sharing also require multiple users to co-manage the privacy of information, the fundamental results generated by this project could be expanded to those collaborative environments beyond social networks. The goal of this project is to seek an effective and flexible mechanism to enable privacy-aware collaborative data sharing in OSNs. To this end, the researchers will first analyze data sharing associated with multiple users in OSNs, and articulate several typical scenarios of privacy conflicts to understand the risks posed by those conflicts. To mitigate risks caused by privacy conflicts, the researchers will investigate a collaborative data sharing mechanism to support the specification and enforcement of multiple privacy concerns. In addition, a systematic conflict detection and resolution mechanism will be created and evaluated with respect to its ability to cope with privacy conflicts occurring in collaborative management of data sharing in OSNs. The conflict resolution in the project attempts to balance the need for privacy protection and users' desire for information sharing by quantitative analysis of privacy risk and sharing loss. Another compelling feature of the proposed approach is the support of both theoretical and empirical analyses on privacy control in OSNs. The researchers will analyze the strategic behaviors of rational users using a game-theoretic model, where each player aims at accommodating her/his privacy concerns as much as possible by adjusting her/his privacy setting in collaborative data sharing in OSNs. Furthermore, the researchers will carry out empirical analysis for practical user behaviors and contrast it with the theoretical analysis in collaborative data sharing, articulating the gap between the theoretic model and real user behaviors. More details about this project, including experimental data and curricular materials can be found on the project website (www.cs.clemson.edu/~hongxih/projects/gpc).