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Full Description
This book examines the uses and potential risks of location-based services (LBS) in the context of big data, with a focus on location privacy protection methods.
The growth of the mobile Internet and the popularity of smart devices have spurred the development of LBS and related mobile applications. However, the misuse of sensitive location data could compromise the physical and communication security of associated devices and nodes, potentially leading to privacy breaches. This book explores the potential risks to the location privacy of mobile users in the context of big data applications. It discusses the latest methods and implications of location privacy from different perspectives. The author offers case studies of three applications: statistical disclosure and privacy protection of location-based big data using a centralized differential privacy model; a user location perturbation mechanism based on a localized differential privacy model; and terminal location perturbation using a geo-indistinguishability model. Linking recent developments in three-dimensional positioning and artificial intelligence, the book also predicts future trends and provides insights into research issues in location privacy.
This title will be a valuable resource for researchers, students, and professionals interested in location-based services, privacy computing and protection, wireless network security, and big data security.
Contents
1. Introduction 2. Location-based Services and Location Privacy Protection 3. Dynamic Statistical Publishing and Privacy Protection of Location-based Big Data via Adaptive Sampling and Grid Clustering 4. Localized Location Privacy Protection based on Optimized Random Response 5. Achieving Location Privacy Protection via Geo-indistinguishability and Location Semantics 6. Conclusion
