Location Privacy in Pervasive Computing
IEEE Pervasive Computing
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Enhancing Security and Privacy in Traffic-Monitoring Systems
IEEE Pervasive Computing
Dynamics of Inter-Meeting Time in Human Contact Networks
ASONAM '09 Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining
Inferring long-term user properties based on users' location history
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Dynamic privacy management in pervasive sensor networks
AmI'10 Proceedings of the First international joint conference on Ambient intelligence
Exploring social context with the wireless rope
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part I
Big brother knows your friends: on privacy of social communities in pervasive networks
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
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WiFi base stations are increasingly deployed in both public spaces and private companies, and the increase in their density poses a significant threat to the privacy of connected users. Prior studies have provided evidence that it is possible to infer the social ties of users from their location and co-location traces but they lack one important component: the comparison of the inference accuracy between an internal attacker (e.g., a curious application running on a mobile device) and a realistic external eavesdropper in the same field trial. In this paper, we experimentally show that such an eavesdropper is able to infer the type of social relationships between mobile users better than an internal attacker. Moreover, our results indicate that by exploiting the underlying social community structure of mobile users, the accuracy of the inference attacks doubles. Based on our findings, we propose countermeasures to help users protect their privacy against eavesdroppers.