Electronic Resource

Big Data Privacy Preservation for Cyber-Physical Systems

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
1908001785	EB0002419	005.7 Big	Central Library	Available

Detail Information

Series Title

SpringerBriefs in Electrical and Computer Engineering

Call Number

005.7 Big

Publisher

Switzerland : Springer Cham., 2019

Collation

IX, 73p.:Ill

Language

English

ISBN/ISSN

978-3-030-13370-2

Classification

005.7

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

1

Subject(s)

Cooperating objects (Computer systems)

Specific Detail Info

-

Statement of Responsibility

BRF

Other version/related

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