Degree Type

Thesis

Date of Award

2009

Degree Name

Master of Science

Department

Computer Science

First Advisor

Ying Cai

Abstract

Advances in wireless communication and positioning technology have made possible the identification of a user's location and hence collect large volumes of personal location data. While such data are useful to many organizations, making them publicly accessible is generally prohibited because location data may imply sensitive private information. This thesis investigates the challenges inherent in publishing location data while preserving location privacy of data subjects. Since location data itself may lead to subject re-identification, simply removing user identity from location data is not sufficient for anonymity preservation, and other measures must be employed. We provide a literature survey and discuss limitations of related work on this problem. We then propose a novel location depersonalization technique that produces efficient depersonalization of large volumes of location data. The proposed technique is evaluated using simulation. Our study shows that it is possible to guarantee a desired level of anonymity protection while allowing accurate location data to be published.

Copyright Owner

Girish Lingappa

Language

en

Date Available

2012-04-06

File Format

application/pdf

File Size

30 pages

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