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SpringerBriefs in Electrical and Computer Engineering

Big Data Privacy Preservation for Cyber-Physical Systems

Authors: Pan, M., Wang, J., Errapotu, S.M., Zhang, X., Ding, J., Han, Z.

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  • This book addresses the processing limitations of massive data without disclosing users’ privacy in various CPS applications, a major concern in real-time big data analytics to achieve better data management and effective decision making

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eBook $44.99
price for USA in USD (gross)
  • ISBN 978-3-030-13370-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $59.99
price for USA in USD
  • ISBN 978-3-030-13369-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This SpringerBrief mainly focuses on effective big data analytics for CPS, and addresses the privacy issues that arise on various CPS applications. The authors develop a series of privacy preserving data analytic and processing methodologies through data driven optimization based on applied cryptographic techniques and differential privacy in this brief. This brief also focuses on effectively integrating the data analysis and data privacy preservation techniques to provide the most desirable solutions for the state-of-the-art CPS with various application-specific requirements.  

Cyber-physical systems (CPS) are the “next generation of engineered systems,” that integrate computation and networking capabilities to monitor and control entities in the physical world. Multiple domains of CPS typically collect huge amounts of data and rely on it for decision making, where the data may include individual or sensitive information, for e.g., smart metering, intelligent transportation, healthcare, sensor/data aggregation, crowd sensing etc. This brief assists users working in these areas and contributes to the literature by addressing data privacy concerns during collection, computation or big data analysis in these large scale systems. Data breaches result in undesirable loss of privacy for the participants and for the entire system, therefore identifying the vulnerabilities and developing tools to mitigate such concerns is crucial to build high confidence CPS.

This Springerbrief targets professors, professionals and research scientists working in Wireless Communications, Networking, Cyber-Physical Systems and Data Science. Undergraduate and graduate-level  students interested in Privacy Preservation of state-of-the-art Wireless Networks and Cyber-Physical Systems will use this Springerbrief as a study guide.  


Table of contents (6 chapters)

Table of contents (6 chapters)

Buy this book

eBook $44.99
price for USA in USD (gross)
  • ISBN 978-3-030-13370-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $59.99
price for USA in USD
  • ISBN 978-3-030-13369-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Big Data Privacy Preservation for Cyber-Physical Systems
Authors
Series Title
SpringerBriefs in Electrical and Computer Engineering
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
The Author(s), under exclusive license to Springer Nature Switzerland AG
eBook ISBN
978-3-030-13370-2
DOI
10.1007/978-3-030-13370-2
Softcover ISBN
978-3-030-13369-6
Series ISSN
2191-8112
Edition Number
1
Number of Pages
IX, 73
Number of Illustrations
2 b/w illustrations, 23 illustrations in colour
Topics