Modeling Adversarial Behavior Against Mobility Data Privacy

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