De-anonymization attack on geolocated data
作者：
Highlights：
• We propose an inference attack that can re-identify anonymous mobility data.
• The attack is based on a mobility model called Mobility Markov Chain (MMC).
• We design several distances between MMC to evaluate their impact in the de-anonymization.
• Experiments on real datasets demonstrate the efficiency of the attack.
• The results shows that anonymizing mobility data is a difficult task.
摘要
•We propose an inference attack that can re-identify anonymous mobility data.•The attack is based on a mobility model called Mobility Markov Chain (MMC).•We design several distances between MMC to evaluate their impact in the de-anonymization.•Experiments on real datasets demonstrate the efficiency of the attack.•The results shows that anonymizing mobility data is a difficult task.
论文关键词：Privacy,Geolocation,Inference attack,De-anonymization
论文评审过程：Received 19 September 2013, Revised 15 October 2013, Accepted 9 April 2014, Available online 18 April 2014.
论文官网地址：https://doi.org/10.1016/j.jcss.2014.04.024
