Deep learning for security and privacy preservation in IoT / Aaisha Makkar, Neeraj Kumar, editors.
Makkar, Aaisha, editor.; Kumar, Neeraj (Computer scientist), editor.
2021
QA76.9.A25
Available Online

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Details

Title
Deep learning for security and privacy preservation in IoT / Aaisha Makkar, Neeraj Kumar, editors.
ISBN
9789811661860 (electronic bk.)
9811661863 (electronic bk.)
9811661855 (print)
9789811661853 (print)
DOI
https://doi.org/10.1007/978-981-16-6186-0
Published
Singapore : Springer, 2021.
Language
English
Description
1 online resource (1 volume) : illustrations (black and white, and color).
Item Number
10.1007/978-981-16-6186-0 doi
Call Number
QA76.9.A25
Dewey Decimal Classification
005.8
Summary
This book addresses the issues with privacy and security in Internet of things (IoT) networks which are susceptible to cyber-attacks and proposes deep learning-based approaches using artificial neural networks models to achieve a safer and more secured IoT environment. Due to the inadequacy of existing solutions to cover the entire IoT network security spectrum, the book utilizes artificial neural network models, which are used to classify, recognize, and model complex data including images, voice, and text, to enhance the level of security and privacy of IoT. This is applied to several IoT applications which include wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT and connected networks. The book serves as a reference for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Makkar, Aaisha, editor.
Kumar, Neeraj (Computer scientist), editor.
Series
Signals and communication technology.
Available in Other Form
DEEP LEARNING FOR SECURITY AND PRIVACY PRESERVATION IN IOT.
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
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