01545nas a2200169   4500008004100000020001400041245006400055210006400119260000900183300001100192520103400203100002501237700002101262700001501283700001901298856005801317       2020                        eng d  a1558-001600aModeling Adversarial Behavior Against Mobility Data Privacy0 aModeling Adversarial Behavior Against Mobility Data Privacy  c2020  a1 - 143 aPrivacy 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.1 aPellungrini, Roberto1 aPappalardo, Luca1 aSimini, F.1 aMonreale, Anna  uhttps://ieeexplore.ieee.org/abstract/document/9199893