Browsing by Subject "Location-based services"

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    Privacy-preserving location-based services.
    (2010-05) Chow, Chi Yin
    Location-based services (LBS for short) providers require users' current locations to answer their location-based queries, e.g., range and nearest-neighbor queries. Revealing personal location information to potentially untrusted service providers could create privacy risks for users. To this end, our objective is to design a privacy-preserving framework for LBS where users can obtain LBS and preserve their location privacy. In this thesis, we propose privacy-preserving LBS frameworks for different environments: (1) client-server environments in Euclidean space (the Casper system), (2) client-server environments in road networks, (3) mobile peer-to-peer environments, and (4) location monitoring services in wireless sensor networks (the TinyCasper system). In general, these frameworks have two main modules, namely, location anonymization and privacy- aware query processing. The location anonymization module blurs an user's exact location into a cloaked area (or a cloaked road segment set in road network environments) that satisfies the user's privacy requirements. The proposed frameworks support the two most popular privacy requirements, k-anonymity, i.e., a user is indistinguishable among k users, and minimum area Amin (or minimum total length of a cloaked road segment set), i.e., the size of a cloaked area is at least Amin. The user is able to specify his/her privacy requirements in a privacy profile and change the privacy profile at any time. The privacy-aware query processing module is embedded inside a database server to provide LBS based on cloaked areas (or cloaked road segment sets). To prove the concept of our privacy-preserving LBS frameworks, we implement system prototypes for Casper and TinyCasper. For each proposed privacy-preserving LBS framework, we conduct extensive experiments to evaluate the performance of its location anonymization and privacy-aware query processing modules. All experiment results show that the proposed frameworks are scalable and efficient with respect to large numbers of users, large numbers of queries, and various privacy requirements, and they provide high quality services in terms of the accuracy of query answers and the query response time.
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    Towards location-aware news feed and recommendations
    (2014-06) Bao, Jie
    With the advances in positioning techniques, such as GPS, cell-towers and WiFi, users can enjoy location-based services more easily than ever before, e.g., on their smart phones and GPS devices. However, with the popularity of recommendation (e.g., Amazon \& Netflix) and socialization (like Facebook and Twitter) functionalities in the web services, users of location-based services are no longer satisfied with the static results returned from a spatial database. At the same time, more and more spatial information, such as geo-tagged photos and check-ins are generated in the traditional social networking services. As a result, users are calling for the next generation of location-based service, i.e., location aware news feed and recommendations, which can provide the user with the more personalized and socialized services.In this thesis, I present my vision of the next generation of location-aware service, which enables the social networking services with location awareness. First of all, in this thesis, I present the unique properties that location information brings to the traditional social networking and recommendation services. After that, I summarize the potential challenges in building efficient and effective location-aware news feed and recommendation services from both the system and user's perspectives. Then, I present a prototype system, (i.e., Sindbad, a location-aware social networking system), to demonstrate three main services provided in the system, as: 1) location-aware news feed service, which efficiently returns the user with spatial-aware messages from her subscribed friends. 2)~location-aware news ranking services, which provide a set of efficient news ranking and message updating algorithms for the user to get more relevant news, based on her social-spatial preferences. And 3)~location-aware recommendations, which provides suggestions based on the social knowledge from the local experts and the preferences mined from a user's location history. Finally, the thesis is concluded with the overall contributions and some potential further research directions.