Handbook of Big Data Privacy (Record no. 174295)

MARC details
000 -LEADER
fixed length control field 05833nam a22005775i 4500
001 - CONTROL NUMBER
control field 978-3-030-38557-6
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125114.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 200318s2020 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030385576
-- 978-3-030-38557-6
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-030-38557-6
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.9.A25
072 #7 - SUBJECT CATEGORY CODE
Subject category code UR
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code UTN
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM053000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UR
Source thema
072 #7 - SUBJECT CATEGORY CODE
Subject category code UTN
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.8
Edition number 23
245 10 - TITLE STATEMENT
Title Handbook of Big Data Privacy
Medium [electronic resource] /
Statement of responsibility, etc edited by Kim-Kwang Raymond Choo, Ali Dehghantanha.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2020.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2020.
300 ## - PHYSICAL DESCRIPTION
Extent IX, 397 p. 149 illus., 141 illus. in color.
Other physical details online resource.
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-- computer
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-- online resource
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-- text file
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505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Big Data and Privacy : Challenges and Opportunities -- 2. AI and Security of Critical Infrastructure -- 3. Industrial Big Data Analytics: Challenges and Opportunities -- 4. A Privacy Protection Key Agreement Protocol Based on ECC for Smart Grid -- 5. Applications of Big Data Analytics and Machine Learning in the Internet of Things -- 6. A Comparison of State-of-the-art Machine Learning Models for OpCode-Based IoT Malware Detection -- 7. Artificial Intelligence and Security of Industrial Control Systems -- 8. Enhancing Network Security via Machine Learning: Opportunities and Challenges -- 9. Network Security and Privacy Evaluation Scheme for Cyber Physical Systems (CPS) -- 10. Anomaly Detection in Cyber-Physical Systems Using Machine Learning -- 11. Big Data Application for Security of Renewable Energy Resources -- 12. Big-Data and Cyber-Physical Systems in Healthcare: Challenges and Opportunities -- 13. Privacy Preserving Abnormality Detection: A Deep Learning Approach.-14. Privacy and Security in Smart and Precision Farming: A Bibliometric Analysis -- 15. A Survey on Application of Big Data in Fin Tech Banking Security and Privacy -- 16. A Hybrid Deep Generative Local Metric Learning Method For Intrusion Detection -- 17. Malware elimination impact on dynamic analysis: An experimental machine learning approach -- 18. RAT Hunter: Building Robust Models for Detecting Remote Access Trojans Based on Optimum Hybrid Features -- 19. Active Spectral Botnet Detection based on Eigenvalue Weighting -- .
520 ## - SUMMARY, ETC.
Summary, etc This handbook provides comprehensive knowledge and includes an overview of the current state-of-the-art of Big Data Privacy, with chapters written by international world leaders from academia and industry working in this field. The first part of this book offers a review of security challenges in critical infrastructure and offers methods that utilize acritical intelligence (AI) techniques to overcome those issues. It then focuses on big data security and privacy issues in relation to developments in the Industry 4.0. Internet of Things (IoT) devices are becoming a major source of security and privacy concern in big data platforms. Multiple solutions that leverage machine learning for addressing security and privacy issues in IoT environments are also discussed this handbook. 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data protection.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer networks .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data and Information Security.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Engineering and Networks.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Communication Networks.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Choo, Kim-Kwang Raymond.
Relator term editor.
-- (orcid)0000-0001-9208-5336
-- https://orcid.org/0000-0001-9208-5336
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Dehghantanha, Ali.
Relator term editor.
-- (orcid)0000-0002-9294-7554
-- https://orcid.org/0000-0002-9294-7554
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030385569
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030385583
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030385590
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-030-38557-6">https://doi.org/10.1007/978-3-030-38557-6</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

No items available.

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