Hongyu Chen1, Shuyu Li1, *, Zhaosheng Zhang1
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2665-2685, 2020, DOI:10.32604/cmc.2020.010965
Abstract In recent years, mobile Internet technology and location based services have
wide application. Application providers and users have accumulated huge amount of
trajectory data. While publishing and analyzing user trajectory data have brought great
convenience for people, the disclosure risks of user privacy caused by the trajectory data
publishing are also becoming more and more prominent. Traditional k-anonymous
trajectory data publishing technologies cannot effectively protect user privacy against
attackers with strong background knowledge. For privacy preserving trajectory data
publishing, we propose a differential privacy based (k-Ψ)-anonymity method to defend
against re-identification and probabilistic inference attack. The proposed method is
divided… More >
Login
Register
