Social networks (SNs), including Facebook, Twitter and LinkedIn have developed on the Internet to become a leading paradigm of online interaction. SNs have been successful in attracting users, and providing a medium where users can easily share and distribute content. Such open availability of data exposes SN users to a number of security and privacy risks. Current SN architectures adopt a simple user centric policy management approach, where a security aware user is able to specify a policy that manages access to their posted content. However, the majority of users lack appropriate information to make informed privacy decisions.
The goal of this project is to develop a comprehensive and compelling framework that leverages data mining approaches and policies composed by other community members to provide the user with appropriate information required when making policy decisions. The wisdom of the community is aggregated and summarized to assist users when making policy decisions related to user-to-user interactions, and third party applications. The principal intellectual products resulting from this project will be the development of novel policy management frameworks that focuses on both usability, and leverages data mining, recommendations and policy sharing techniques to consult the SN community to aid in enhancing users? privacy policies.
This project has a broad societal impact on new business and community models for sharing on SNs, providing mechanisms that enable users to make more informed access decisions. In addition this project will support graduate and undergraduate students, and will engage K-12 students and enhance their understanding of privacy in SNs.