NeTS

This project aims to develop a substrate called SocialLite that can use online social network data to obtain reliable identity and trust information. This work involves three steps: 1) identifying the rich variety of identity and trust information embedded in online social networks; 2) designing algorithms and software to efficiently and robustly abstract this information as a set of flexible API functions without violating a user?s privacy from large online social networks; and 3) evaluating the usefulness of the API by implementing a few sample applications.

Today, almost every browsing click that users make is collected by numerous trackers associated with a variety of online services (e.g., advertising networks, online social networks, e-commerce platforms). Users have often expressed concern about the lack of privacy and control over their personal data. Nonetheless, despite a substantial effort to expose and control this prevalent behavior, the reality is that users keep accepting updated online privacy policies, which in turn grant the gathering of more personal data.

Despite our growing reliance on mobile phones for a wide range of daily tasks, their operation remains largely opaque even for experts. Mobile users have little insight into how their mobile apps operate and perform in the network, into how (or whether) they protect the information that users entrust to them, and with whom they share user's personal information. A number of previous studies have addressed elements of this problem in a partial fashion, trading off analytic comprehensiveness and deployment scale.