Philip Ginzboorg

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

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.

Inferring social ties in pervasive networks: an on-campus comparative study

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 users. Prior studies have shown that it is possible to infer the social ties between users from their (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 the device) and a realistic external eavesdropper (e.g., a network of sniffing stations) in the same field trial. We experimentally show that such an eavesdropper can infer the type of social ties between mobile users better than an internal attacker.

From the rigid hierarchical to flexible flow-based 5G architecture: Dimensioning issues

This paper analyzes the applicability of typical hierarchical architecture of mobile networks for future 5G systems. In particular, node dimensioning characteristics are evaluated based on 5G requirements. As a result of the evaluation we conclude that more flexible flow-based architecture is needed to handle 5G capacity and delay requirements. We then present the concept of flexible handling of multiple IP flows from a data (user) plane perspective taking into account the existing infrastructure of the Mobile Network Operator (MNO). Finally, implementation aspects of the new concept are briefly discussed.