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Social relationships are a natural basis on which humans make trustdecisions. Online Social Networks (OSNs) are increasingly often used to letusers base trust decisions on the existence and the strength of socialrelationships. While most OSNs allow users to discover the length of the socialpath to other users, they do so in a centralized way, thus requiring them torely on the service provider and reveal their interest in each other. Thispaper presents Social PaL, a system supporting the privacy-preserving discoveryof arbitrary-length social paths between any two social network users. Weovercome the bootstrapping problem encountered in all related prior work,demonstrating that Social PaL allows its users to find all paths of length twoand to discover a significant fraction of longer paths, even when only a smallfraction of OSN users is in the Social PaL system - e.g., discovering 70% ofall paths with only 40% of the users. We implement Social PaL using a scalableserver-side architecture and a modular Android client library, allowingdevelopers to seamlessly integrate it into their apps.

How Far Removed Are You? Scalable Privacy-Preserving Estimation of Social Path Length with Social PaL