Achieving Guaranteed Anonymity in Time-series Location Data

Achieving Guaranteed Anonymity in Time-series Location Data

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Collaborative sensing networks anonymously aggregate location-tagged sensing information from a large number of users to monitor environments. However, sharing anonymous location-tagged sensing information from users raises serious privacy concern. Rendering the location traces anonymous before sharing them with application service providers or third parties often allows an adversary to follow anonymous location updates because a time-series of anonymous location data exhibit a spatio-temporal correlation between successive updates. Prior privacy techniques for location data such as spatial cloaking techniques based on k-anonymity and best-effort algorithms do not meet both data quality and privacy requirements at the same time. This raises the problem of guaranteed anonymity in a dataset of location traces while maintaining high data accuracy and integrity.ready and confident with my Ph.D. thesis defense presentation. Her advices based on the lessons that she learned from NYU, Cornell, and Rockafellar Univ. inspired me througout my Ph.D. life with her. My deepest thanks go to my family PhDsanbsp;...

Title:Achieving Guaranteed Anonymity in Time-series Location Data
Publisher:ProQuest - 2008


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