{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T13:46:58Z","timestamp":1762004818236},"reference-count":0,"publisher":"Privacy Enhancing Technologies Symposium Advisory Board","issue":"4","license":[{"start":{"date-parts":[[2016,7,14]],"date-time":"2016-07-14T00:00:00Z","timestamp":1468454400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p> With the advance of indoor localization technology, indoor location-based services (ILBS) are gaining popularity. They, however, accompany privacy concerns. ILBS providers track the users\u2019 mobility to learn more about their behavior, and then provide them with improved and personalized services. Our survey of 200 individuals highlighted their concerns about this tracking for potential leakage of their personal\/private traits, but also showed their willingness to accept reduced tracking for improved service. In this paper, we propose PR-LBS (Privacy vs. Reward for Location-Based Service), a system that addresses these seemingly conflicting requirements by balancing the users\u2019 privacy concerns and the benefits of sharing location information in indoor location tracking environments. PR-LBS relies on a novel location-privacy criterion to quantify the privacy risks pertaining to sharing indoor location information. It also employs a repeated play model to ensure that the received service is proportionate to the privacy risk. We implement and evaluate PR-LBS extensively with various real-world user mobility traces. Results show that PR-LBS has low overhead, protects the users\u2019 privacy, and makes a good tradeoff between the quality of service for the users and the utility of shared location data for service providers.<\/jats:p>","DOI":"10.1515\/popets-2016-0031","type":"journal-article","created":{"date-parts":[[2016,7,18]],"date-time":"2016-07-18T08:14:59Z","timestamp":1468829699000},"page":"102-122","source":"Crossref","is-referenced-by-count":7,"title":["Privacy vs. Reward in Indoor Location-Based Services"],"prefix":"10.56553","volume":"2016","author":[{"given":"Kassem","family":"Fawaz","sequence":"first","affiliation":[{"name":"University of Michigan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyu-Han","family":"Kim","sequence":"additional","affiliation":[{"name":"Hewlett Packard Labs"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kang G.","family":"Shin","sequence":"additional","affiliation":[{"name":"University of Michigan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"35752","published-online":{"date-parts":[[2016,7,14]]},"container-title":["Proceedings on Privacy Enhancing Technologies"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/content.sciendo.com\/view\/journals\/popets\/2016\/4\/article-p102.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.sciendo.com\/article\/10.1515\/popets-2016-0031","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,20]],"date-time":"2022-07-20T16:29:26Z","timestamp":1658334566000},"score":1,"resource":{"primary":{"URL":"https:\/\/petsymposium.org\/popets\/2016\/popets-2016-0031.php"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7,14]]},"references-count":0,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2016,7,14]]},"published-print":{"date-parts":[[2016,10,1]]}},"alternative-id":["10.1515\/popets-2016-0031"],"URL":"https:\/\/doi.org\/10.1515\/popets-2016-0031","relation":{},"ISSN":["2299-0984"],"issn-type":[{"value":"2299-0984","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,7,14]]}}}