Inferring social ties in academic networks using short-range wireless communications

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State: Public
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Serval ID
serval:BIB_770B8AF71C30
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Title
Inferring social ties in academic networks using short-range wireless communications
Title of the conference
Proceedings of the 12th ACM workshop on Workshop on privacy in the electronic society (WPES)
Author(s)
Bilogrevic I., Huguenin K., Jadliwala M., Lopez F., Hubaux J.-P., Ginzboorg P., Niemi V.
Publisher
ACM
Address
Berlin, Germany
ISBN
978-1-4503-2485-4
Publication state
Published
Issued date
2013
Peer-reviewed
Oui
Pages
179-188
Language
english
Abstract
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.
Create date
30/11/2016 16:55
Last modification date
20/08/2019 14:34
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