@inproceedings{eabf3dc169f64d08ac3c51b435fc920e,
title = "EPLA: Efficient personal location anonymity",
abstract = "A lot of researchers utilize side-information, such as map which is likely to be exploited by some attackers, to protect users{\textquoteright} location privacy in location-based service (LBS). However, current technologies universally model the side-information for all users. We argue that the side-information is personal for every user. In this paper, we propose an efficient method, namely EPLA, to protect the users{\textquoteright} privacy using visit probability. We selected the dummy locations to achieve k-anonymity according to personal visit probability for users{\textquoteright} queries. AKDE greatly reduces the computational complexity compared with KDE approach. We conduct comprehensive experimental study on the realistic Gowalla data sets and the experimental results show that EPLA obtains fine privacy performance and efficiency.",
keywords = "Anonymity, Cloaking region, KDE, LBS, Privacy",
author = "Dapeng Zhao and Kai Zhang and Yuanyuan Jin and Xiaoling Wang and Hung, \{Patrick C.K.\} and Wendi Ji",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.",
year = "2016",
doi = "10.1007/978-3-319-45817-5\_21",
language = "英语",
isbn = "9783319458168",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "263--275",
editor = "Kyuseok Shim and Kai Zheng and Guanfeng Liu and Feifei Li",
booktitle = "Web Technologies and Applications - 18th Asia-Pacific Web Conference, APWeb 2016, Proceedings",
address = "德国",
}