Graduation Semester and Year

2011

Language

English

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Engineering

First Advisor

Matthew Wright

Abstract

In recent years, mobile devices and smartphones enabled with GPS and Inter-net access have become extremely common. People use these devices as they woulda personal computer for easy access to information. Location Based Services (LBS)provide customized information based on a user's geographic location that has beenretrieved from a dedicated spatial database such as Google Places, Yahoo's LocalSearch Web Services and Yelp.com. This information can include nearby hotels andrestaurants, gas stations, banks or other Points of Interest (POIs). Since most searchengines and databases are known to store previous queries in order to improve futuresearch results and other data analysis on previous search queries, many researchershave expressed concerns and proposed solutions to protect a user's location privacy.Research has shown that a significant amount of information, such as medical condi-tions, political or religious affiliations and more can be inferred based on a person'sprevious location tracks. Many methods proposed by researchers rely on the use oftrusted third parties such as Anonymizing Servers, other nearby mobile devices, orthe LBS itself. CAP (Context-Aware Privacy), introduced in 2008 by A. Pingley et.al., is a system that was designed to protect a user's location without having to rely on a trusted third party or interfere with the operation of the LBS. A desktop proto-type was made, yet it was never implemented on a mobile device or smartphone untilnow. Preliminary tests of CAP with lower privacy settings proved to be effective,although when the privacy settings were increased, the results seemed to deteriorate.Closer examinations of the algorithm indicate that it is effective when compressingcontextual map data for use by a mobile device, as well as effective perturbation ofthe user's location. The POI results returned from the LBS tell a different story.While the POI results at low privacy levels seemed to be accurate (i.e. the POIsreturned from the LBS are in fact the POIs that are closest to the user), when theprivacy settings were increased, the results would degrade (i.e. the POIs returnedwere, as expected, further away from the user's actual location). This is effective inthe sense that the user's actual location is not able to be divulged to an adversary,but is not very effective in terms of usability and convenience for the user. In thisthesis, we review CAP and several other proposed methods of location privacy in-tended for use with mobile devices. We have implemented CAP on a smartphone inits proposed method and evaluate its results, followed by modifications in order togain more accurate POI results from publicly available LBS.

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

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