This paper presents a study that aims to answer two important questions related to targeted location-sharing privacy attacks: (1) given a group of users and their social graph, is it possible to predict which among them is likely to reveal most about their whereabouts, and (2) given a user, is it possible to predict which among her friends knows most about her whereabouts. To answer these questions we analyse the privacy policies of users of a realtime location sharing application, in which users actively shared their location with their contacts. The results show that users who are central to their network are more likely to reveal most about their whereabouts. Furthermore, we show that the friend most likely to know the whereabouts of a specific individual is the one with most common contacts and/or greatest number of contacts.
They identified the best potential friend of a node i. Informally, the best potential friend of a node i is the node k that when linked to i, it provides the highest increase in the PageRank of i. In REF ) the authors conduct a study that aims to answer two questions: i) given a group of users and their social graph, is it possible to predict who among them is likely to reveal most about the whereabouts of anyone in the group?
Who's your best friend?: targeted privacy attacks In location-sharing social networks
UbiComp '11
Computer Science