Can I read SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention (SCADA‐Based IDs Security) on EtoBox?

SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention (SCADA‐Based IDs Security) by Almalawi, Abdulmohsen; Tari, Zahir; Fahad, Adil; Yi, Xun is a scholarly article available to read on EtoBox.

What is SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention (SCADA‐Based IDs Security) about?

"This book provides insights into issues of SCADA security. Chapter 1 discusses how potential attacks against traditional IT can also be possible against SCADA systems. Chapter 2 gives background information on SCADA systems, their architectures, and main components. In Chapter 3, the authors describe SCADAVT, a framework for a SCADA security testbed based on virtualization technology. Chapter 4 introduces an approach called kNNVWC to find the k-nearest neighbours in large and high dimensional data. Chapter 5 describes an approach called SDAD to extract proximity-based detection rules, from unlabelled SCADA data, based on a clustering-based technique. In Chapter 6, the authors explore an approach called GATUD which finds a global and efficient anomaly threshold. The book concludes with a summary of the contributions made by this book to the extant body of research, and suggests possible directions for future research"-- Provided by publisher

Author

Almalawi, Abdulmohsen; Tari, Zahir; Fahad, Adil; Yi, Xun

Publisher

Wiley & Sons, Limited, John

Published

2020

Language

EN

ISBN

9781119606352