{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T15:56:07Z","timestamp":1776182167329,"version":"3.50.1"},"reference-count":16,"publisher":"Association for Computing Machinery (ACM)","issue":"13","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2016,9]]},"abstract":"<jats:p>The release of detailed taxi trips has motivated numerous useful studies, but has also triggered multiple privacy attacks on individuals' trips. Despite these attacks, no tools are available for systematically analyzing the privacy risk of released trajectory data. While, recent studies have proposed mechanisms to publish synthetic mobility data with provable privacy guarantees, the questions on -- 1) how to explain the theoretical privacy guarantee to non-privacy experts; and 2) how well private data preserves the properties of ground truth, remain unclear. To address these issues, we propose a system --- VisDPT that provides rich visualization of sensitive information in trajectory databases and helps data curators understand the impact on utility due to privacy preserving mechanisms. We believe VisDPT will enable data curators to take informed decisions while publishing sanitized data.<\/jats:p>","DOI":"10.14778\/3007263.3007291","type":"journal-article","created":{"date-parts":[[2016,11,1]],"date-time":"2016-11-01T13:47:47Z","timestamp":1478008067000},"page":"1489-1492","source":"Crossref","is-referenced-by-count":10,"title":["A demonstration of VisDPT"],"prefix":"10.14778","volume":"9","author":[{"given":"Xi","family":"He","sequence":"first","affiliation":[{"name":"Duke University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nisarg","family":"Raval","sequence":"additional","affiliation":[{"name":"Duke University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashwin","family":"Machanavajjhala","sequence":"additional","affiliation":[{"name":"Duke University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2016,9]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Taxi trajectory open dataset Tsinghua university China. http:\/\/sensor.ee.tsinghua.edu.cn 2009.  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Riding with the stars: Passenger privacy in the nyc taxicab dataset , 2014 . neustar Research. Riding with the stars: Passenger privacy in the nyc taxicab dataset, 2014."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1403657111"},{"key":"e_1_2_1_12_1","volume-title":"with a vengeance","author":"Schneider T. W.","year":"2015","unstructured":"T. W. Schneider . Analyzing 1.1 billion nyc taxi and uber trips , with a vengeance , 2015 . T. W. Schneider. Analyzing 1.1 billion nyc taxi and uber trips, with a vengeance, 2015."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/HPCC.2014.195"},{"key":"e_1_2_1_14_1","volume-title":"CoRR","author":"Xu M.","year":"2014","unstructured":"M. Xu , J. Wu , Y. Du , H. Wang , G. Qi , K. Hu , and Y. Xiao . Discovery of important crossroads in road network using massive taxi trajectories . CoRR , 2014 . M. Xu, J. Wu, Y. Du, H. Wang, G. Qi, K. Hu, and Y. Xiao. Discovery of important crossroads in road network using massive taxi trajectories. 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