Social relationships are a natural basis on which humans make trust decisions. Online Social Networks (OSNs) are increasingly often used to let users base trust decisions on the existence and the strength of social relationships. While most OSNs allow users to discover the length of the social path to other users, they do so in a centralized way, thus requiring them to rely on the service provider and reveal their interest in each other. This paper presents Social PaL, a system supporting the privacy-preserving discovery of arbitrary-length social paths between any two social network users. We overcome the bootstrapping problem encountered in all related prior work, demonstrating that Social PaL allows its users to find all paths of length two and to discover a significant fraction of longer paths, even when only a small fraction of OSN users is in the Social PaL system - e.g., discovering 70 of all paths with only 40 of the users. We implement Social PaL using a scalable server-side architecture and a modular Android client library, allowing developers to seamlessly integrate it into their apps.
Smokescreen @cite_29 , SMILE @cite_18 , and PIKE @cite_53 support secure private device-to-device handshake and proximity-based communication. introduce SDDR @cite_33 , which allows a device to establish a secure encounter -- i.e., a secret key -- with every device in short radio range, and can be used to recognize previously encountered users, while providing strong unlinkability guarantees. The EnCore platform @cite_42 builds on SDDR to provide privacy-preserving interaction between nearby devices, as well as event-based communication for mobile social applications.
@cite_18 @cite_33 @cite_29 @cite_42 @cite_53
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Conventional mobile social services such as Loopt and Google Latitude rely on two classes of trusted relationships: participants trust a centralized server to manage their location information and trust between users is based on existing social relationships. Unfortunately, these assumptions are not secure or general enough for many mobile social scenarios: centralized servers cannot always be relied upon to preserve data confidentiality, and users may want to use mobile social services to establish new relationships. To address these shortcomings, this paper describes SMILE, a privacy-preserving "missed-connections" service in which the service provider is untrusted and users are not assumed to have pre-established social relationships with each other. At a high-level, SMILE uses short-range wireless communication and standard cryptographic primitives to mimic the behavior of users in existing missed-connections services such as Craigslist: trust is founded solely on anonymous users' ability to prove to each other that they shared an encounter in the past. We have evaluated SMILE using protocol analysis, an informal study of Craigslist usage, and experiments with a prototype implementation and found it to be both privacy-preserving and feasible. Presence-sharing is an emerging platform for mobile applications, but presence-privacy remains a challenge. Privacy controls must be flexible enough to allow sharing between both trusted social relations and untrusted strangers. In this paper, we present a system called SmokeScreen that provides flexible and power-efficient mechanisms for privacy management. Broadcasting clique signals, which can only be interpreted by other trusted users, enables sharing between social relations; broadcasting opaque identifiers (OIDs), which can only be resolved to an identity by a trusted broker, enables sharing between strangers. Computing these messages is power-efficient since they can be pre-computed with acceptable storage costs. In evaluating these mechanisms we first analyzed traces from an actual presence-sharing application. Four months of traces provide evidence of anonymous snooping, even among trusted users. We have also implemented our mechanisms on two devices and found the power demands of clique signals and OIDs to be reasonable. A mobile phone running our software can operate for several days on a single charge. Mobile social apps provide sharing and networking opportunities based on a user's location, activity, and set of nearby users. A platform for these apps must meet a wide range of communication needs while ensuring users' control over their privacy. In this paper, we introduce EnCore, a mobile platform that builds on secure encounters between pairs of devices as a foundation for privacy-preserving communication. An encounter occurs whenever two devices are within Bluetooth radio range of each other, and generates a unique encounter ID and associated shared key. EnCore detects nearby users and resources, bootstraps named communication abstractions called events for groups of proximal users, and enables communication and sharing among event participants, while relying on existing network, storage and online social network services. At the same time, EnCore puts users in control of their privacy and the confidentiality of the information they share. Using an Android implementation of EnCore and an app for event-based communication and sharing, we evaluate EnCore's utility using a live testbed deployment with 35 users. Online collaboration tools such as Google+, Face-book or Dropbox have become an important and ubiquitous mediator of many human interactions. In the virtual world, they enable secure interaction by controlling access to shared resources. Yet relying on them to support synchronous direct interactions, such as face-to-face meetings, might be suboptimal as they require reliable online connectivity and even then often introduce delays. A much more efficient way of co-located resource sharing is the use of local communications, such as ad-hoc WiFi. Yet setting up the necessary encryption and authentication mechanisms is often cumbersome. In this paper, we present PIKE, a key exchange protocol that minimizes this configuration effort. PIKE piggybacks the exchange of keys on top of an existing service infrastructure. To support encryption or authentication without Internet connection, PIKE relies on triggers for upcoming personal interactions and exchanges keys before they take place. To evaluate PIKE, we present two example applications and we perform an experimental as well as an analytical analysis of its characteristics. The evaluation indicates that PIKE is broadly applicable, scales well enough to support larger events and provides a level of security that is (at least) comparable to the one provided by the underlying service.