A K-Anonymity Privacy-Preserving Location Monitoring System for Wireless Sensor Networks with Nymble Secure System
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International Journal of Computer & Organization Trends (IJCOT) |  |
| © 2012 by IJCOT Journal | ||
| Volume-2 Issue-2 |
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| Year of Publication : 2012 | ||
| Authors : -Gayathri M,Bharathi M. |
Citation
-Gayathri M,Bharathi M. A K-Anonymity Privacy-Preserving Location Monitoring System for Wireless Sensor Networks with Nymble Secure System . International Journal of Computer & organization Trends (IJCOT), V2(2):6-13 Mar - Apr, 2012, ISSN 2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.
Abstract
Anonymizing wireless sensor networks allow users to access services privately by using a series of routers to hide the client’s IP address from the server. As a result, administrators block all known exit nodes of anonymizing networks, denying anonymous access to misbehaving. To address this problem, servers can “blacklist” misbehaving users, thereby blocking users without compromising their anonymity. Monitoring personal locations with a potentially untrusted server poses privacy threats to the monitored individuals, a privacy-preserving location monitoring system for wireless sensor networks is adopted. Two innetwork location anonymization algorithms are considered, namely, resource and quality-aware algorithms, that aim to enable the system to provide high-quality location monitoring services for system users, while preserving personal location privacy. Both algorithms rely on the well established k-anonymity privacy concept, that is, a person is indistinguishable among k persons, to enable trusted sensor nodes to provide the aggregate location information of monitored persons. Each aggregate location is in a form of a monitored area A along with the number of monitored persons residing in A, where A contains at least k persons. The resource-aware algorithm aims to minimize communication and computational cost, while the quality-aware algorithm aims to maximize the accuracy of the aggregate locations by minimizing their monitored areas. To utilize the aggregate location information and to provide location monitoring services, a spatial histogram approach is used that estimates the distribution of the monitored persons based on the gathered aggregate location information. Then, the estimated distribution is used to provide location monitoring services through answering range queries.
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Keywords
Location privacy, wireless sensor networks, location monitoring system, aggregate query processing, spatial histogram, Anonymous blacklisting, privacy, Misbehaving users.