Map Services Based on Multiple Mix-zones with Location Privacy Protection over Road Network

The evolution of technological era has marked the expansion of using map services (Google map, Baidu map etc.) in mobile vehicles over road networks. This is also accompanied by a threat to user’s personal information disclosure like geographic locations (GPS coordinates) or addresses as users share...

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Veröffentlicht in:Wireless personal communications 2017-11, Vol.97 (2), p.2617-2632
Hauptverfasser: Arain, Qasim Ali, Deng, Zhongliang, Memon, Imran, Zubedi, Asma, Mangi, Farman Ali
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Sprache:eng
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Zusammenfassung:The evolution of technological era has marked the expansion of using map services (Google map, Baidu map etc.) in mobile vehicles over road networks. This is also accompanied by a threat to user’s personal information disclosure like geographic locations (GPS coordinates) or addresses as users share their locations and queries to obtain desired services. It is observed that existing techniques proposing methods for mix-zones location privacy protection are unfeasible to implement when applied to provide location privacy for map service users. In this paper, a comprehensive method for multiple mix-zones location privacy protection (MMLPP) is specially designed for map services on mobile vehicles over road networks. This method enables mobile vehicle users to query a route between two endpoints on the map, without revealing any sensitive location and queries information. The basic idea is to strategically endpoint to nearby ones, such that: (1) the semantic meanings encoded in these endpoints (e.g., their GPS coordinates) change much, i.e., location privacy is protected; (2) the routes returned by map services change little, i.e., services usability are maintained. Specifically, a mobile client first privately retrieves point of interests (POIs) close to the original endpoints, and then selects two POIs as the shifted endpoints satisfying the property of Geo-Indistinguishability. We evaluate our MMLPP approach road network application by GTMobiSim on different scales of map services, and conduct experiments with real traces. The results show that MMLPP strikes a good balance between location privacy and service usability.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-017-4626-0