Название: Protecting Location Privacy in the Era of Big dаta: A Technical Perspective
Автор: Yan Yan, Adnan Mahmood, Quan Z. Sheng
Издательство: CRC Press
Год: 2025
Страниц: 137
Язык: английский
Формат: pdf (true), epub
Размер: 27.8 MB

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 (AI), the book also predicts future trends and provides insights into research issues in location privacy.

Nowadays, the magnitude of data that needs to be processed in a timely manner in order to extract useful information has jumped from TB level to PB level or even EB level. With the deep application of intelligent computing devices in all areas of human work and life, the rate of data growth is increasing day by day, and the base of data is also increasing. An ordinary computer can carry out GB-level data computing in an acceptable time. Famous distributed big data processing tools such as Hadoop, Spark, Storm, etc. have been widely used. Facebook, the famous Internet company, has launched Presto, a tool that can perform EB-level real-time big data processing.

Big Data contains inestimable value and information. Analyses, mining, and applications based on Big Data have attracted the attention of governments, industries, and research sectors all over the world. However, compared with the overall scale of Big Data, the value of individual data is very low, i.e., low value density. Only by aggregating a large amount of data for processing can valuable information be mined from it, reflecting the value of Big Data computing.

Big Data not only implies potentially huge commercial value but is also a new tool for enhancing national governance capacity and improving public services. The application of Big Data for scientific analysis, prediction, and mining not only contributes to technological innovation and application development in many fields, such as social demographic surveys, public health research, urban transportation and road planning, social opinion analysis, business model investigation, agricultural yield and disease prediction, and bio-informatics analysis, but also expands the application of personal data through the openness and sharing of big data, and expands the scope and quality of social services by promoting the integration of resources.

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.