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Deep learning techniques for IOT sec...

Abdel-Basset, Mohamed.

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Deep learning techniques for IOT security and privacy

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning techniques for IOT security and privacy/ by Mohamed Abdel-Basset ... [et al.].
other author:	Abdel-Basset, Mohamed.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	xxi, 257 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter 1, Conceptualization of Security, Forensics, and Privacy of Internet of Things -- Chapter 2, Internet of Things, Preliminaries and Foundations -- Chapter 3, Internet of Things Security Requirements, Threats, Countermeasures -- Chapter 4, Digital Forensics in Internet of Things -- Chapter 5, Supervised Deep Learning for Secure Internet of Things -- Chapter 6, Unsupervised Deep Learning for Secure Internet of Things -- Chapter 7, Semi-supervised Deep Learning for Secure Internet of Things -- Chapter 8, Reinforcement Learning for Secure Internet of Things -- Chapter 9, Federated Learning for Privacy-Preserving Internet of Things -- Chapter 10, Challenges, Opportunities, and Future Prospects.
Contained By:	Springer Nature eBook
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-3-030-89025-4
ISBN:	9783030890254

Deep learning techniques for IOT security and privacy
Deep learning techniques for IOT security and privacy[electronic resource] /by Mohamed Abdel-Basset ... [et al.]. - Cham :Springer International Publishing :2022. - xxi, 257 p. :ill., digital ;24 cm. - Studies in computational intelligence,v. 9971860-9503 ;. - Studies in computational intelligence ;v. 997..

Chapter 1, Conceptualization of Security, Forensics, and Privacy of Internet of Things -- Chapter 2, Internet of Things, Preliminaries and Foundations -- Chapter 3, Internet of Things Security Requirements, Threats, Countermeasures -- Chapter 4, Digital Forensics in Internet of Things -- Chapter 5, Supervised Deep Learning for Secure Internet of Things -- Chapter 6, Unsupervised Deep Learning for Secure Internet of Things -- Chapter 7, Semi-supervised Deep Learning for Secure Internet of Things -- Chapter 8, Reinforcement Learning for Secure Internet of Things -- Chapter 9, Federated Learning for Privacy-Preserving Internet of Things -- Chapter 10, Challenges, Opportunities, and Future Prospects.

This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.

ISBN: 9783030890254

Standard No.: 10.1007/978-3-030-89025-4doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Deep learning techniques for IOT security and privacy
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245 0 0 $a Deep learning techniques for IOT security and privacy $h [electronic resource] / $c by Mohamed Abdel-Basset ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xxi, 257 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-9503 ; $v v. 997
505 0 $a Chapter 1, Conceptualization of Security, Forensics, and Privacy of Internet of Things -- Chapter 2, Internet of Things, Preliminaries and Foundations -- Chapter 3, Internet of Things Security Requirements, Threats, Countermeasures -- Chapter 4, Digital Forensics in Internet of Things -- Chapter 5, Supervised Deep Learning for Secure Internet of Things -- Chapter 6, Unsupervised Deep Learning for Secure Internet of Things -- Chapter 7, Semi-supervised Deep Learning for Secure Internet of Things -- Chapter 8, Reinforcement Learning for Secure Internet of Things -- Chapter 9, Federated Learning for Privacy-Preserving Internet of Things -- Chapter 10, Challenges, Opportunities, and Future Prospects.
520 $a This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.
650 0 $a Machine learning. $3 533906
650 0 $a Internet of things $x Security measures. $3 3217048
650 1 4 $a Data Engineering. $3 3409361
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Abdel-Basset, Mohamed. $3 3494506
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773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v. 997. $3 3593003
856 4 0 $u https://doi.org/10.1007/978-3-030-89025-4
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)