Overview
One of the first handbooks that provides interdisciplinary coverage of security, privacy and forensics knowledge in the field of big data and IoT security, privacy, and forensics
Presents an up-to-date view of existing and emerging security, privacy, and forensics challenges, research opportunities and solutions
Introduces the technical information regarding cyber threats applicable to big data platforms and offers technical solutions to address those threats for the researcher and software developers to build automated systems that address security, trust and privacy issues in big data platforms
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Table of contents (19 chapters)
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Front Matter
Keywords
About this book
The second part of this handbook is focused on privacy and security issues in different layers of big data systems. It discusses about methods for evaluating security and privacy of big data systems on network, application and physical layers. This handbook elaborates on existing methods to use data analytic and AI techniques at different layers of big data platforms to identify privacy and security attacks. The final part of this handbook is focused on analyzing cyber threats applicable to the big data environments. It offers an in-depth review of attacks applicable to big data platforms in smart grids, smart farming, FinTech, and health sectors. Multiple solutions are presented to detect, prevent and analyze cyber-attacks and assess the impact of malicious payloads to those environments.
This handbook provides information for security and privacy experts in most areas of big data including; FinTech, Industry 4.0, Internet of Things, Smart Grids, Smart Farming and more. Experts working in big data, privacy, security, forensics, malware analysis, machine learning and data analysts will find this handbook useful as a reference. Researchers and advanced-level computer science students focused on computer systems, Internet of Things, Smart Grid, Smart Farming, Industry 4.0 and network analysts will also find this handbook useful as a reference.
Editors and Affiliations
About the editors
Ali Dehghantanha is the director of Cyber Science Lab in the University of Guelph, Ontario, Canada. His lab is focused on building AI-powered solutions to support cyber threat attribution, cyber threat hunting and digital forensics tasks in Internet of Things (IoT), Industrial IoT, and Internet of Military of Things (IoMT) environments. Ali has served for more than a decade in a variety of industrial and academic positions with leading players in cyber security and AI. Prior to joining UofG, he has served as a Sr. Lecturer in the University of Sheffield - UK. He is an EU Marie-Curie Fellow alumnus and an IEEE Sr. member. He received his Ph.D. in Security in Computing in 2011 and his M.Sc. in Security in Computing in 2008.
Bibliographic Information
Book Title: Handbook of Big Data Privacy
Editors: Kim-Kwang Raymond Choo, Ali Dehghantanha
DOI: https://doi.org/10.1007/978-3-030-38557-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-38556-9Published: 19 March 2020
Softcover ISBN: 978-3-030-38559-0Published: 19 March 2021
eBook ISBN: 978-3-030-38557-6Published: 18 March 2020
Edition Number: 1
Number of Pages: IX, 397
Number of Illustrations: 8 b/w illustrations, 141 illustrations in colour
Topics: Security, Computer Systems Organization and Communication Networks, Artificial Intelligence, Information Systems and Communication Service