Région Rhône-Alpes ARC 7
Most smartphones possess a Wi-Fi interface which continuously sends frames containing a header field, the MAC address, which acts as a unique identifier of the device. Wi-Fi tracking is a technology which takes advantage of that fact to gather information in order to perform statistics about people passing in a place: number of visitors, duration and frequency of visits, travel path, etc.
An easy and wide-spread method to store such valuable information is to store the MAC addresses with basic or even no encryption. Such method poses privacy problems, as a person having access to such information (legitimately or not) may infer more information about passing people than what is necessary for statistics.
The subject of this PhD work is to propose methods to limit the privacy problems of the Wi-Fi tracking technology. More specifically, methods to store information without personnal identifiers are studied. Ultimately, we aim to propose services similar to existing Wi-Fi tracking tools, augmented with privacy-by-design. We seek to propose a trade-off between privacy and usefulness of the data.
As a first step, we make a survey of the different methods to anonymize MAC addresses: hashes, hashes and troncation, bitmaps, different kinds of bloom filters...