{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T09:03:47Z","timestamp":1758272627164},"reference-count":10,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>\n            Location privacy-preserving mechanisms (LPPMs) have been extensively studied for protecting a user's location in location-based services. However, when user's perturbed locations are released continuously, existing LPPMs may not protect users' sensitive\n            <jats:italic>spatiotemporal event<\/jats:italic>\n            , such as \"visited hospital in the last week\" or \"regularly commuting between location 1 and location 2 every morning and afternoon\" (it is easy to infer that locations 1 and 2 may be home and office). In this demonstration, we demonstrate PriSTE for protecting spatiotemporal event privacy in continuous location release. First, to raise users' awareness of such a new privacy goal, we design an interactive tool to demonstrate how accurate an adversary could infer a secret spatiotemporal event from a sequence of locations or even LPPM-protected locations. The attendees can find that some spatiotemporal events are quite risky and even these state-of-the-art LPPMs do not always protect spatiotemporal event privacy. Second, we demonstrate how a user can use PriSTE to automatically or manually convert an LPPM for location privacy into one protecting spatiotemporal event privacy in continuous location-based services. Finally, we visualize the trade-off between privacy and utility so that users can choose appropriate privacy parameters in different application scenarios.\n          <\/jats:p>","DOI":"10.14778\/3352063.3352086","type":"journal-article","created":{"date-parts":[[2019,9,18]],"date-time":"2019-09-18T18:36:11Z","timestamp":1568831771000},"page":"1866-1869","source":"Crossref","is-referenced-by-count":11,"title":["PriSTE"],"prefix":"10.14778","volume":"12","author":[{"given":"Yang","family":"Cao","sequence":"first","affiliation":[{"name":"Kyoto University, Japan"}]},{"given":"Yonghui","family":"Xiao","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Li","family":"Xiong","sequence":"additional","affiliation":[{"name":"Emory University"}]},{"given":"Liquan","family":"Bai","sequence":"additional","affiliation":[{"name":"Emory University"}]},{"given":"Masatoshi","family":"Yoshikawa","sequence":"additional","affiliation":[{"name":"Kyoto University, Japan"}]}],"member":"320","published-online":{"date-parts":[[2019,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2508859.2516735"},{"key":"e_1_2_1_2_1","first-page":"1606","volume-title":"ICDE","author":"Cao Y."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.14778\/3352063.3352086"},{"key":"e_1_2_1_4_1","first-page":"1","volume-title":"TAMC","author":"Dwork C.","year":"2008"},{"key":"e_1_2_1_5_1","volume-title":"The long road to computational location privacy: A survey","author":"Primault V.","year":"2018"},{"key":"e_1_2_1_6_1","first-page":"156","volume-title":"Proceedings on Privacy Enhancing Technologies","volume":"2017","author":"Recabarren R.","year":"2017"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-22479-0_8"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813640"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.14778\/3137765.3137804"},{"issue":"2","key":"e_1_2_1_10_1","first-page":"32","article-title":"a collaborative social networking service among user, location and trajectory","volume":"33","author":"Zheng Y.","year":"2010","journal-title":"IEEE Data Eng. Bull."}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3352063.3352086","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:40:55Z","timestamp":1672224055000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3352063.3352086"}},"subtitle":["protecting spatiotemporal event privacy in continuous location-based services"],"short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":10,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2019,8]]}},"alternative-id":["10.14778\/3352063.3352086"],"URL":"https:\/\/doi.org\/10.14778\/3352063.3352086","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2019,8]]}}}