SCADA security : machine learning concepts for intrusion detection and prevention : SCADA-based IDs security

• Main Authors: Almalawi, Abdulmohsen, (Author), Tari, Zahir, 1961- (Author), Fahad, Adil, (Author), Yi, Xun, (Author)
• Format: eBook
• Language: English
• Published: Hoboken, NJ, USA : Wiley, 2021.
• Edition: First edition.
• Series: Wiley series on parallel and distributed computing.
• Subjects: Supervisory control systems.; Automatic control > Security measures.; Intrusion detection systems (Computer security); Machine learning.; elektronické knihy; electronic books
• ISBN: 9781119606383; 1119606381; 9781119606352; 1119606357; 9781119606079; 1119606071; 9781119606031
• Physical Description: 1 online resource (xvi, 196 pages) : illustrations (chiefly color)
• Access: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty

"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"--