Geosocial networks are online social networks centered on the locations of subscribers and businesses. Providing input to targeted advertising, profiling social network users becomes an important source of revenue. Its natural reliance on personal information introduces a trade-off between user privacy and incentives of participation for businesses and geosocial network providers. In this paper we introduce location centric profiles (LCPs), aggregates built over the profiles of users present at a given location. We introduce PROFILR, a suite of mechanisms that construct LCPs in a private and correct manner. We introduce iSafe, a novel, context aware public safety application built on PROFILR . Our Android and browser plugin implementations show that PROFILR is efficient: the end-to-end overhead is small even under strong correctness assurances.
Online Social Networks (OSNs) encourage users to create an online presence that reflects their offline identity. OSNs create the illusion that these online accounts correspond to the correct offline person, but in reality the OSN lacks the resources to detect impersonation. We propose that OSN users identify each other based on interaction and experience. We believe that impersonation can be thwarted by users who possess exclusive shared knowledge, secret information shared only between a pair of OSN friends. We describe existing protocols that use shared secrets to exchange public keys without revealing those secrets to attackers. We present results from a user study on Facebook to show that users do share exclusive knowledge with their Facebook friends and attackers are rarely able to guess that knowledge. Finally, we show that friend identification can be extended using a web of trust built on the OSN friend graph. Online social networks (OSNs) are attractive applications which enable a group of users to share data and stay connected. Facebook, Myspace, and Twitter are among the most popular applications of OSNs where personal information is shared among group contacts. Due to the private nature of the shared information, data privacy is an indispensable security requirement in OSN applications. In this paper, we propose a privacy-preserving scheme for data sharing in OSNs, with efficient revocation for deterring a contact's access right to the private data once the contact is removed from the social group. In addition, the proposed scheme offers advanced features such as efficient search over encrypted data files and dynamic changes to group membership. With slight modification, we extend the application of the proposed scheme to anonymous online social networks of different security and functional requirements. The proposed scheme is demonstrated to be secure, effective, and efficient. Today's online social networking (OSN) sites do little to protect the privacy of their users' social networking information. Given the highly sensitive nature of the information these sites store, it is understandable that many users feel victimized and disempowered by OSN providers' terms of service. This paper presents Lockr, a system that improves the privacy of centralized and decentralized online content sharing systems. Lockr offers three significant privacy benefits to OSN users. First, it separates social networking content from all other functionality that OSNs provide. This decoupling lets users control their own social information: they can decide which OSN provider should store it, which third parties should have access to it, or they can even choose to manage it themselves. Such flexibility better accommodates OSN users' privacy needs and preferences. Second, Lockr ensures that digitally signed social relationships needed to access social data cannot be re-used by the OSN for unintended purposes. This feature drastically reduces the value to others of social content that users entrust to OSN providers. Finally, Lockr enables message encryption using a social relationship key. This key lets two strangers with a common friend verify their relationship without exposing it to others, a common privacy threat when sharing data in a decentralized scenario. This paper relates Lockr's design and implementation and shows how we integrate it with Flickr, a centralized OSN, and BitTorrent, a decentralized one. Our implementation demonstrates Lockr's critical primary benefits for privacy as well as its secondary benefits for simplifying site management and accelerating content delivery. These benefits were achieved with negligible performance cost and overhead. Social networking services (SNS), which provide the application with the most probably highest growth rates in the Internet today, raise serious security concerns, especially with respect to the privacy of their users. Multiple studies have shown the vulnerability of these services to breaches of privacy and to impersonation attacks mounted by third parties, however the centralized storage at the providers of SNS represents an additional quite significant weakness that so far has not satisfyingly been addressed. In this paper we show the feasibility of “Safebook”, our proposal for the provision of a competitive social networking service, which solves these vulnerabilities by its decentralized design, leveraging on the real life relationships of its users and means of cryptography.