Mining social interactions in connection traces of a campus Wi-Fi network

Le résumé fourni par la source

Wi-Fi technologies have become one of the most popular means for Internet access. As a result, the use of mobile devices has become ubiquitous and instrumental for society. A device can be identified through its MAC address within an autonomous system. Although some devices attempt to anonymize MAC addresses via randomization, these techniques are not used once the device is associated to the network [7]. As a result, device identification poses a privacy problem in large-scale (e.g., campus-wide) Wi-Fi deployments [5]: if the mobile device can be located, the user who carries that device can also be located. In turn, location information leads to the possibility to extract private knowledge from Wi-Fi users, like social interactions, movement habits, and so forth.

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