AI-Enabled Threat Detection and Security Analysis for Industrial IoT /

This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and...

Full description

Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Karimipour, Hadis (Editor), Derakhshan, Farnaz (Editor)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:	1st ed. 2021.
Subjects:	Computer networks > Security measures. Computer engineering. Internet of things. Embedded computer systems. Artificial intelligence. Machine learning. Mobile and Network Security. Cyber-physical systems, IoT. Artificial Intelligence. Machine Learning. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Artificial Intelligence for Threat Detection and Analysis in Industrial IoT: Applications and Challenges
Complementing IIoT Services through AI: Feasibility and Suitability
Data Security and Privacy in Industrial IoT
Blockchain Applications in the Industrial Internet of Things
Application of Deep Learning on IoT-enabled Smart Grid Monitoring
Cyber Security of Smart Manufacturing Execution Systems: A Bibliometric Analysis
The Role of Machine Learning in IIoT Through FPGAs
Deep Representation Learning for Cyber-Attack Detection in Industrial IoT
Classification and Intelligent Mining of Anomalies in Industrial IoT
A Snapshot Ensemble Deep Neural Network Model for Attack Detection in Industrial Internet of Things
Privacy Preserving Federated Learning Solution for Security of Industrial Cyber Physical Systems
A Multi-Stage Machine Learning Model for Security Analysis in Industrial Control System
A Recurrent Attention Model for Cyber Attack Classification.