Social media involve many shared items, such as photos, which may concern more than one user. The challenge is that users’ individual privacy preferences for the same item may conflict, so an approach that simply merges in some way the users’ privacy preferences may provide unsatisfactory results. Previous proposals to deal with the problem were either time-consuming or did not consider compromises to solve these conflicts (e.g., by considering unilaterally imposed approaches only). We propose a negotiation mechanism for users to agree on a compromise for these conflicts. The second challenge we address in this article relates to the exponential complexity of such a negotiation mechanism. To address this, we propose heuristics that reduce the complexity of the negotiation mechanism and show how substantial benefits can be derived from the use of these heuristics through extensive experimental evaluation that compares the performance of the negotiation mechanism with and without these heuristics. Moreover, we show that one such heuristic makes the negotiation mechanism produce results fast enough to be used in actual social media infrastructures with near-optimal results.
Online social networks (OSNs) have experienced tremendous growth in recent years and become a de facto portal for hundreds of millions of Internet users. These OSNs offer attractive means for digital social interactions and information sharing, but also raise a number of security and privacy issues. While OSNs allow users to restrict access to shared data, they currently do not provide any mechanism to enforce privacy concerns over data associated with multiple users. To this end, we propose an approach to enable the protection of shared data associated with multiple users in OSNs. We formulate an access control model to capture the essence of multiparty authorization requirements, along with a multiparty policy specification scheme and a policy enforcement mechanism. Besides, we present a logical representation of our access control model that allows us to leverage the features of existing logic solvers to perform various analysis tasks on our model. We also discuss a proof-of-concept prototype of our approach as part of an application in Facebook and provide usability study and system evaluation of our method. Topology-based access control is today a de-facto standard for protecting resources in On-line Social Networks (OSNs) both within the research community and commercial OSNs. According to this paradigm, authorization constraints specify the relationships (and possibly their depth and trust level) that should occur between the requestor and the resource owner to make the first able to access the required resource. In this paper, we show how topology-based access control can be enhanced by exploiting the collaboration among OSN users, which is the essence of any OSN. The need of user collaboration during access control enforcement arises by the fact that, different from traditional settings, in most OSN services users can reference other users in resources (e.g., a user can be tagged to a photo), and therefore it is generally not possible for a user to control the resources published by another user. For this reason, we introduce collaborative security policies, that is, access control policies identifying a set of collaborative users that must be involved during access control enforcement. Moreover, we discuss how user collaboration can also be exploited for policy administration and we present an architecture on support of collaborative policy enforcement. As the popularity of social networks expands, the information users expose to the public has potentially dangerous implications for individual privacy. While social networks allow users to restrict access to their personal data, there is currently no mechanism to enforce privacy concerns over content uploaded by other users. As group photos and stories are shared by friends and family, personal privacy goes beyond the discretion of what a user uploads about himself and becomes an issue of what every network participant reveals. In this paper, we examine how the lack of joint privacy controls over content can inadvertently reveal sensitive information about a user including preferences, relationships, conversations, and photos. Specifically, we analyze Facebook to identify scenarios where conflicting privacy settings between friends will reveal information that at least one user intended remain private. By aggregating the information exposed in this manner, we demonstrate how a user's private attributes can be inferred from simply being listed as a friend or mentioned in a story. To mitigate this threat, we show how Facebook's privacy model can be adapted to enforce multi-party privacy. We present a proof of concept application built into Facebook that automatically ensures mutually acceptable privacy restrictions are enforced on group content.