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Privacy Conscious Screening Framework for Frequently Moving Objects
Abstract
The fundamental problem in any monitoring system is
when and how a mobile client should send location updates to the server, because it determines three principal performance measures such as monitoring accuracy, efficiency, and privacy. In this paper the clients considered as, are privacy conscious. The PCS is the comprehensive framework that addresses the issue of location updating holistically with monitoring accuracy, efficiency, and privacy altogether. This framework extends from the previous work by introducing a common privacy model, and therefore, suits realistic
scenarios. We incorporate other types of queries into the framework, such as spatial joins and aggregate queries. We optimize the performance of the framework by sequentially optimizing the queries but maintain the safe region accumulated by the queries optimized so far.
Keywords
References
N.Beckmann, H. Kriegel, R. Schneider, and B. Seeger, “The R*- Tree: An Efficient and Robust Access Method for Points and Rectangles,” Proc. ACM SIGMOD, pp. 322-331, 1990.
R.Benetis, C.S. Jensen, G. Karciauskas, and S. Saltenis, “Nearest Neighbor and Reverse Nearest Neighbor Queries for Moving Objects,” Proc. Int’l Database Eng. And Applications Symp. (IDEAS), 2002.
J.Beresford and F. Stajano, “Location Privacy in Pervasive Computing,” IEEE Pervasive Computing, vol. 2, no. 1, pp. 46-55, Jan.-Mar. 2003.
J. Broch, D.A. Maltz, D. Johnson, Y.-C. Hu, and J. Jetcheva,
“APerformance Comparison of Multi-Hop Wireless Ad Hoc
NetworkRouting Protocols,” Proc. ACM/IEEE MobiCom, pp. 85-
,1998.
Y.Cai, K.A.Hua, and G. Cao, “Processing Range-MonitoringQueries on Heterogeneous Mobile Objects,” Proc. IEEE Int’l Conf.Mobile Data Management (MDM), 2004.
Chen, D. DeWitt, F. Tian, and Y. Wang, “NiagaraCQ: A Scalable Continuous Query System for Internet Databases,” Proc. ACM SIGMOD, 2000.
R. Cheng, D.V. Kalashnikov, and S. Prabhakar, “Querying Imprecise Data in Moving Object Environments,” IEEE Trans. Knowledge and Data Eng., vol. 16, no. 9, pp. 1112- 1127, Sept. 2004.
H.D. Chon, D. Agrawal, and A.E. Abbadi, “Range and kNN Query Processing for Moving Objects in Grid Model,” ACM/ Kluwer MONET, vol. 8, no. 4, pp. 401-412, 2003.
C.-Y. Chow, M.F. Mokbel, and X. Liu, “A Peer-to-Peer Spatial Cloaking Algorithm for Anonymous Location-Based Services,” Proc. ACM Int’l Symp. Geographic Information Systems (GIS), pp. 171-178, 2006.
B. Gedik and L. Liu, “Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms,” IEEE Trans. on Mobile Computing, vol. 7, no. 1, pp. 1-18, Jan. 2008.
G. Ghinita, P. Kalnis, and S. Skiadopoulos, “Mobihide: A Mobile Peerto- Peer System for Anonymous Location-Based Queries,” Proc. Int’l Symp. Spatial and Temporal Databases (SSTD), 2007.
M. Gruteser and D. Grunwald, “Anonymous Usage of Location- Based Services through Spatial and Temporal Cloaking,” Proc. MobiSys, 2003.
Haibo Hu, Jianliang Xu, Senior Member, “PAM: An Efficient and Privacy-Aware Monitoring Framework for Continuously Moving Objects,” IEEE Transactions on knowledge and data engineering, vol. 22, no. 3, march 2010.
G.Iwerks, H.Samet, and K.Smith, “Continuous k-Nearest Neighbor Queries for Continuously Moving Points with Up- dates,” Proc. Int’l Conf. Very Large Data Bases (VLDB), 2003.
D.Pfoser and C.S. Jensen, “Capturing the Uncertainty of Moving- Objects Representations,” Proc. Int’l Conf. Scientific and Statistical Database Management (SSDBM), 1999.
Bamba, B., Liu, L., Pesti, P., Wang, T.: Supporting anonymous location queries in mobile environments with privacy grid. In: Proceedings of the International World Wide Web Conference, WWW (2008).
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