Privacy Preserving on Trajectories Created by Wi-Fi Connections in a University Campus

In universities, it is common to find many access points widely distributed through the campus aiming to cover most of the area with Wi-Fi signal. Each time a connection between a device and an access point is performed, the data generated by that action (e.g. location, student identification and time) are stored in a log file. This file allow us to track back the trajectories of the students inside the universities, ordering this data by time. With the identification attribute of the student, it is possible to join it with quasi-identifiers present in the university systems. Publication of such data may put the privacy of university students in risk. Given that, this article proposes a method of anonymization called Mix beta-k-anonymity. This technique provides a set of possible trajectories of a group of people with the same quasi-identifiers. After the application of this method, it is showed that with the right choice of the quasi-identifier is possible to anonymize the trajectories making possible the disclosure for operational mobility research on campus.