SCADA security : machine learning concepts for intrusion detection and prevention /
Abdulmohsen Almalawi, King Abdulaziz University, Zahir Tari, RMIT University, Adil Fahad, Al Baha University, Xun Yi, Royal Melbourne Institute of Technology.
- 1 online resource.
- Wiley series on parallel and distributed computing .
- Wiley series on parallel and distributed computing. .
Includes bibliographical references and index.
Introduction -- Background -- SCADA-Based Security Testbed -- Efficient k-Nearest Neighbour Approach Based on Various-Widths Clustering -- SCADA Data-Driven Anomaly Detection -- A Global Anomaly Threshold to Unsupervised Detection -- Threshold Password-Authenticated Secret Sharing Protocols -- Conclusion.
"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"--
Supervisory control systems. Automatic control--Security measures. Intrusion detection systems (Computer security) Machine learning. Intrusion detection systems (Computer security) Machine learning Supervisory control systems