@inproceedings{7690599a16cb42b7b1c70083e1ec682a,
title = "Towards Understanding the Advertiser's Perspective of Smartphone User Privacy",
abstract = "Many smartphone apps routinely gather various private user data and send them to advertisers. Despite recent study on protection mechanisms and analysis on apps' behavior, the understanding about the consequences of such privacy losses remains limited. In this paper we investigate how much an advertiser can infer about users' social and community relationships by combining data from multiple applications and across many users. After one month's user study involving about 200 most popular Android apps, we find that an advertiser can infer 90\% of the social relationships. We further propose a privacy leakage inference framework and use real mobility traces and Foursquare data to quantify the consequences of privacy leakage. We find that achieving 90\% inference accuracy of the social and community relationships requires merely 3 weeks' user data. The discoveries underscore the importance of early adoption of privacy protection mechanisms.",
keywords = "Privacy, Smartphone, Social relationship",
author = "Yan Wang and Yingying Chen and Fan Ye and Jie Yang and Hongbo Liu",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 35th IEEE International Conference on Distributed Computing Systems, ICDCS 2015 ; Conference date: 29-06-2015 Through 02-07-2015",
year = "2015",
month = jul,
day = "22",
doi = "10.1109/ICDCS.2015.37",
language = "English",
series = "Proceedings - International Conference on Distributed Computing Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "288--297",
booktitle = "Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems, ICDCS 2015",
}