caa a22 4500 445331828 CHVBK 20180317142739.0 cr unu---uuuuu 170323e20110701xx s 000 0 eng 10.1007/s10707-010-0117-0 doi (NATIONALLICENCE)springer-10.1007/s10707-010-0117-0 Query-aware location anonymization for road networks [Elektronische Daten] [Chi-Yin Chow, Mohamed Mokbel, Jie Bao, Xuan Liu] Recently, several techniques have been proposed to protect the user location privacy for location-based services in the Euclidean space. Applying these techniques directly to the road network environment would lead to privacy leakage and inefficient query processing. In this paper, we propose a new location anonymization algorithm that is designed specifically for the road network environment. Our algorithm relies on the commonly used concept of spatial cloaking, where a user location is cloaked into a set of connected road segments of a minimum total length ${\cal L}$ including at least ${\cal K}$ users. Our algorithm is "query-aware” as it takes into account the query execution cost at a database server and the query quality, i.e., the number of objects returned to users by the database server, during the location anonymization process. In particular, we develop a new cost function that balances between the query execution cost and the query quality. Then, we introduce two versions of our algorithm, namely, pure greedy and randomized greedy, that aim to minimize the developed cost function and satisfy the user specified privacy requirements. To accommodate intervals with a high workload, we introduce a shared execution paradigm that boosts the scalability of our location anonymization algorithm and the database server to support large numbers of queries received in a short time period. Extensive experimental results show that our algorithms are more efficient and scalable than the state-of-the-art technique, in terms of both query execution cost and query quality. The results also show that our algorithms have very strong resilience to two privacy attacks, namely, the replay attack and the center-of-cloaked-area attack. Springer Science+Business Media, LLC, 2010 Location privacy nationallicence Shared execution nationallicence Location-based services nationallicence Spatial network databases nationallicence GIS nationallicence Chow Chi-Yin Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China aut Mokbel Mohamed Department of Computer Science and Engineering, University of Minnesota, 55455, Minneapolis, MN, USA aut Bao Jie Department of Computer Science and Engineering, University of Minnesota, 55455, Minneapolis, MN, USA aut Liu Xuan IBM Thomas J. Watson Research Center, 10532, Hawthorne, NY, USA aut GeoInformatica Springer US; http://www.springer-ny.com 15/3(2011-07-01), 571-607 1384-6175 15:3<571 2011 15 10707 https://doi.org/10.1007/s10707-010-0117-0 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10707-010-0117-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Chow Chi-Yin Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China aut NATIONALLICENCE 700 1- Mokbel Mohamed Department of Computer Science and Engineering, University of Minnesota, 55455, Minneapolis, MN, USA aut NATIONALLICENCE 700 1- Bao Jie Department of Computer Science and Engineering, University of Minnesota, 55455, Minneapolis, MN, USA aut NATIONALLICENCE 700 1- Liu Xuan IBM Thomas J. Watson Research Center, 10532, Hawthorne, NY, USA aut NATIONALLICENCE 773 0- GeoInformatica Springer US; http://www.springer-ny.com 15/3(2011-07-01), 571-607 1384-6175 15:3<571 2011 15 10707 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer