Cache Management Techniques for Privacy Preserving Location-based Services
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01-04-2010, 09:07 PM

In order to access location-based services, mobile users have to disclose their exact locations to service providers. However, adversaries could collect the location information for purposes against mobile usersâ„¢ privacy. There are existing solutions for privacy protection by utilizing the K-anonymity model. However, the computational and communication costs are high. This research proposes cache management techniques for further improving user privacy protection, saving computational power, and decreasing communication costs.
Presented By:
Yu Chen
Jie Bao
Wei-Shinn Ku
Jiun-Long Huang

As a result of recent advances in wireless technologies, more and more personal mobile devices (e.g., cell phones, PDAs, etc.) possess the ability to access the Internet ubiquitously. In addition, Global Positioning System (GPS) receiver modules gradually become a standard component in new generation handheld devices. Consequently, novel location based services (LBS) allow users to launch location-dependent queries ubiquitously. Sample queries of such location based services include find me the nearest ATM and show me the gas station with the lowest price within one mile. In order to fulfill these queries, mobile users have to reveal their current locations to service providers. However, service providers may disclose the trajectory of a certain user to attackers which decreases the dependability of LBS. For protecting mobile userâ„¢s privacy, recent research in [12] proposed a framework for location based services without compromising location privacy by leveraging the K-anonymity concept [15]. In order to implement the K-anonymity mechanism, the framework contains a trusted server to collect user location information and perform cloaking procedures. Then, the trusted server will send the location- dependent query along with the cloaked spatial area to service providers to retrieve query results. The returned query solutions will be sent back to individual users by the trusted server as well. Since the trusted server has the knowledge of all query results, we propose to store them in memory and use the cached data to answer future queries. Our solution has two main advantages. First, user privacy protection can be further improved, because the trusted server does not have to forward every query to service providers and it is much more difficult for adversaries to launch correlation attacks [3]. Second, with our cache management techniques, fewer queries have to be answered by service providers. Consequently, computational resources and communication costs can be effectively saved. The rest of the paper is organized as follows: Section 2 surveys the related work of privacy protected query processing. Our own system design is detailed in Section 3. The experimental results are presented in Section 4. We conclude this paper in section 5, and we also raise some open issues for future research.

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