Social Inference Risk Modeling in Mobile and Social Applications

Abstract

Abstract-The emphasis of emerging mobile and Web 2.0 applications on collaboration and communication increases threats to user privacy. A serious, yet under-researched privacy risk results from social inferences about user identity, location and other personal information. In this paper, after analyzing the social inference problem theoretically, we assess the extent of the risk to users of computer-mediated communication and location based applications through 1) a laboratory experimentation, 2) a mobile phone field study, and 3) simulation. Our experimentation involved the use of 530 user-created profiles and a 292-subject laboratory chat-study between strangers. The field study explored the patterns of collocation and anonymity of 165 users using a location-aware mobile-phone survey tool. The empirical data was then utilized to populate large-scale simulations of the social inference risk. The work validates the theoretical model, highlights the seriousness of the social inference risk, and shows how the extent and nature of the risk differs for different classes of social computing applications. We conclude with a discussion of the system design implications.

How did you know that about me? Protecting users against unwanted inferences

“…The results suggested that Method 2 was almost as accurate as Method 3 in the realm of computer-mediated communication and proximity-based applications [11,28]. This means that context and community of users allows to effectively model background knowledge for a specific context.…”

“…More details on calculating the conditional probabilities and information entropy can be found in [11,28] where the authors also set thresholds for information entropy based on users' preferences. If the information entropy is lower than its threshold, there is a high inference risk.…”

“…We developed a framework [27,28] to model and reliably predict social inference risk. As seen before, social inferences happen as a result of low information entropy.…”

“…Background knowledge can be estimated using the following different methods listed here with increasing levels of accuracy [11,28].…”

“…If the information entropy is lower than its threshold, there is a high inference risk. Therefore, instantaneous and historical inference functions are based on instantaneous and historical information entropies [11,28].…”