Modeling Adversarial Behavior Against Mobility Data Privacy

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TitleModeling Adversarial Behavior Against Mobility Data Privacy
Publication TypeJournal Article
Year of Publication2020
AuthorsPellungrini, R, Pappalardo, L, Simini, F, Monreale, A
JournalIEEE Transactions on Intelligent Transportation SystemsIEEE Transactions on Intelligent Transportation Systems
Pagination1 - 14
Date Published2020
ISBN Number1558-0016

Privacy risk assessment is a crucial issue in any privacy-aware analysis process. Traditional frameworks for privacy risk assessment systematically generate the assumed knowledge for a potential adversary, evaluating the risk without realistically modelling the collection of the background knowledge used by the adversary when performing the attack. In this work, we propose Simulated Privacy Annealing (SPA), a new adversarial behavior model for privacy risk assessment in mobility data. We model the behavior of an adversary as a mobility trajectory and introduce an optimization approach to find the most effective adversary trajectory in terms of privacy risk produced for the individuals represented in a mobility data set. We use simulated annealing to optimize the movement of the adversary and simulate a possible attack on mobility data. We finally test the effectiveness of our approach on real human mobility data, showing that it can simulate the knowledge gathering process for an adversary in a more realistic way.

Short TitleIEEE Transactions on Intelligent Transportation Systems