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.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Academic, Postgraduate, Professional Practice & Development, Professional Reference, Undergraduate Advanced, and Undergraduate Core
Illustrationen
10 s/w Tabellen, 45 s/w Zeichnungen, 4 s/w Photographien bzw. Rasterbilder, 49 s/w Abbildungen
10 Tables, black and white; 45 Line drawings, black and white; 4 Halftones, black and white; 49 Illustrations, black and white
Maße
Höhe: 260 mm
Breite: 183 mm
Dicke: 12 mm
Gewicht
ISBN-13
978-1-032-89988-6 (9781032899886)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Yan Yan is a Professor of the School of Computer and Communication, Lanzhou University of Technology, China. Her research interests include, but are not limited to, privacy preserving data collection, privacy preserving data publishing, blockchain transaction privacy protection, and multimedia information security.
Adnan Mahmood is a Lecturer in Computing-IoT and Networking at the School of Computing, Macquarie University, Sydney, Australia. His research interests include, but are not limited to, the Internet of Things (primarily, the Internet of Vehicles), Trust Management, Software-Defined Networking, and the Next Generation Heterogeneous Wireless Networks.
Quan Z. Sheng is a Distinguished Professor and Head of School of Computing at Macquarie University, Australia. He is ranked by Microsoft Academic as one of the Most Impactful Authors in Services Computing (ranked Top 5 of All Time worldwide) and in the Web of Things (ranked Top 20 All Time).
Autor*in
Macquarie University
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
