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Location Cloaking for Location Privacy Protection and Location Safety Protection Ge Xu Iowa State University

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Location Cloaking for Location Privacy Protection and Location Safety Protection Ge Xu Iowa State University Iowa State University Capstones, Theses and Graduate Theses and Dissertations Dissertations 2010 Location cloaking for location privacy protection and location safety protection Ge Xu Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/etd Part of the Computer Sciences Commons Recommended Citation Xu, Ge, "Location cloaking for location privacy protection and location safety protection" (2010). Graduate Theses and Dissertations. 11628. https://lib.dr.iastate.edu/etd/11628 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Location cloaking for location privacy protection and location safety protection by Ge (Toby) Xu A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major: Computer Science Program of Study Committee: Ying Cai, Major Professor Ahmed Kamal Leslie Miller Wallapak Tavanapong Wensheng Zhang Iowa State University Ames, Iowa 2010 ii DEDICATION To my parents and my wife - Without whose love and support I would not have been able to complete this work iii TABLE OF CONTENTS ACKNOWLEDGEMENTS ............................... v ABSTRACT ....................................... vi CHAPTER1. Introduction .............................. 1 CHAPTER2. Relatedwork .............................. 4 2.1 Regulation and policy-based approaches for location dataprotection . 4 2.2 AnonymoususesofLBSs............................ 6 2.3 Non-locationexposureusesofLBS . ... 10 2.4 Trajectoryperturbation . ... 11 2.5 Trajectoryanonymization. ... 12 2.6 Privacy-aware opportunistic sensing and monitoring . ............ 13 2.7 Anonymousroutinginadhocnetworks . ... 14 CHAPTER 3. Location privacy protection in LBSs . ...... 19 3.1 Feeling-basedprivacymodeling . .... 20 3.2 Locationcloakingtechniques. .... 23 3.2.1 Systemoverview ............................ 23 3.2.2 Singlelocationsamplecloaking . .. 25 3.2.3 In-advancetrajectorycloaking . ... 27 3.2.4 On-the-flytrajectorycloaking . .. 29 3.3 Simulations ................................... 32 3.3.1 Singlelocationsamplecloaking . .. 34 iv 3.3.2 Trajectorycloaking. .. .. .. .. .. .. .. 35 3.4 Experiments................................... 40 3.4.1 Serverandclientuserinterface. ... 42 3.4.2 Experimentalresults . .. .. .. .. .. .. .. 43 CHAPTER 4. Location safety protection in ad hoc networks . ......... 46 4.1 Locationcloakingfor locationsafetyprotection . ........... 47 4.1.1 Safetylevel............................... 49 4.1.2 Locationcloakingtechniques . 50 4.1.3 Analysis ................................ 58 4.1.4 Performancestudy ........................... 60 4.2 Locationsecurerouting. .. 66 4.2.1 Safelink ................................ 68 4.2.2 LSR................................... 72 4.2.3 Performanceevaluation. 78 CHAPTER5. ConclusionandFutureWork . 84 5.1 SummaryofContributions . 84 5.2 FutureResearch................................. 85 BIBLIOGRAPHY .................................... 87 v ACKNOWLEDGEMENTS I am extremely lucky that I get support, encouragement, and inspiration from many people. Without them this work would not have been possible. My greatest gratitude goes to my advisor Dr. Ying Cai for his guidance and consistent support. His knowledgeable and wise discussions have inspired the ideas of all the work in this dissertation. When facing obstacles, I am lucky that he has always been there helping me find the right direction. From him I have learned how to find problems, generate solutions, make presentations, and overall how to be a researcher in computer science. Thank you, Dr. Cai! I would also like to thank other members of my committee, Dr. Ahmed Kamal, Dr. Leslie Miller, Dr. Wallapak Tavanapong and Dr. Wensheng Zhang for their time and input. Specif- ically, I would like to thank their insightful comments which help me clarify my ideas and highlight my contributions in this dissertation. I am greatly thankful to my lab mates, Kihwan Kim, Ashwin S. Natarajan, and Patricio Galdames for their collaboration during this research and contributions to this dissertation. I wish to thank Jiang Tian, Taiming Feng, Xia Wang, Chuang Wang, Ru He, Wei Zhang, Hsin-yi Jiang for their support and assistance during my study. Finally, my deep gratitude goes to my wife (Liu Hong) and my parents (Liguang Du and Rongsheng Xu) for their love, sacrifice and support during my life. vi ABSTRACT Many applications today rely on location information, yet disclosing such information can present heightened privacy and safety risks. A person’s whereabouts, for example, may reveal sensitive private information such as health condition and lifestyle. Location information also has the potential to allow an adversary to physically locate and destroy a subject, which is particularly concerned in digital battlefields. This research investigates two problems. The first one is location privacy protection in location-based services. Our goal is to provide a desired level of guarantee that the location data collected by the service providers cannot be correlated with restricted spaces such as home and office to derive who’s where at what time. We propose 1) leveraging historical lo- cation samples for location depersonalization and 2) allowing a user to express her location privacy requirement by identifying a spatial region. With these two ideas in place, we develop a suite of techniques for location-privacy aware uses of location-based services, which can be either sporadic or continuous. An experimental system has been implemented with these tech- niques. The second problem investigated in this research is location safety protection in ad hoc networks. Unlike location privacy intrusion, the adversary here is not interested in finding the individual identities of the nodes in a spatial region, but simply wants to locate and de- stroy them. We define the safety level of a spatial region as the inverse of its node density and develop a suite of techniques for location safety-aware cloaking and routing. These schemes allow nodes to disclose their location as accurately as possible, while preventing such informa- tion from being used to identify any region with a safety level lower than a required threshold. The performance of the proposed techniques is evaluated through analysis and simulation. 1 CHAPTER 1. Introduction With the continuous price dropping and miniaturization of positioning systems such as GPS, more and more applications in wireless networks have taken advantage of location in- formation of wireless users and devices in their design and development. However, disclosing location information can presents heightened privacy and safety risks. In the aspect of pri- vacy, physical destinations such as medical clinics may indicate a person’s health problems. Likewise, regular stops at certain types of places may be linked directly to one’s lifestyles or political associations. In the aspect of safety, knowing the position of a wireless device allows an adversary to locate and physically destroy the subject, which is particularly concerned in digital battlefields. Our research in this thesis aims to address the above threats presented by location exposure. Specifically, we investigate two problems. The first one is location privacy protection in the context of location-based services (LBSs). Too use an LBS, a user needs to submit her location to the service provider, which may not be trustworthy in keeping the information in confidential. Even if a user replaces her real-world identity with a pseudonym, the anonymous location information may still be correlated with restricted spaces such as house and office for subject re-identification. Our research focuses on this problem known as restricted space identification, and investigates location depersonalization for the purpose of location privacy protection. Specifically, given an anonymous location disclosed in a service request, we want to prevent an adversary from deriving who was in the location at the time of the service request. Toward this goal, we propose to explore users’ historical location samples, each called a footprint, for location depersonalization. A spatial region with K different footprints means it 2 has been visited by K different people. When a user requests a service, her location is reported as such a region instead of her accurate position. Therefore, even if an adversary manages to identify all these visitors using restricted spaces, he willnotknowwhich of them was insidethe area at the time of the service request. In addition to location depersonalization, we address the challenge of modeling location privacy requirement. With the traditional K-anonymity model, a user needs to specify a value of K as her privacy requirement. This is problematic, because privacy is about feeling, and it is awkward for one to scale her feeling using a number. Our solution circumvents this problem by allowing a user to identify a public region, such as a shopping mall, which she would feel comfortable that it is reported as her location should she request a service inside it. This region is then used as her privacy requirement – each location disclosed on her behalf needs to be at least as popular as that area. Compared to choosing
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