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

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

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
All Resources
Metamorphosis of Industrial IoT using Deep Leaning
Deep Learning Models and their Architectures for Computer Vision Applications: A Review
IoT Data Security with Machine Learning Blockchain: Risks and Countermeasures
A Review on Cyber Crimes on the Internet of Things
Deep learning framework for anomaly detection in IoT enabled systems
Anomaly Detection using Unsupervised Machine Learning Algorithms
Game Theory Based Privacy Preserving Approach for Collaborative Deep Learning in IoT
Deep Learning based security preservation of IoT: An industrial machine health monitoring scenario
Deep learning Models: An Understandable Interpretable Approaches.

Browse Subjects

Show more subjects...

Statistics

from
to
Export