Almalawi, Abdulmohsen,
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"--
9781119606383 1119606381 9781119606352 1119606357 9781119606079 1119606071
2020027877
Supervisory control systems.
Automatic control--Security measures.
Intrusion detection systems (Computer security)
Machine learning.
Intrusion detection systems (Computer security)
Machine learning
Supervisory control systems
Electronic books.
TJ222
629.8/95583
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"--
9781119606383 1119606381 9781119606352 1119606357 9781119606079 1119606071
2020027877
Supervisory control systems.
Automatic control--Security measures.
Intrusion detection systems (Computer security)
Machine learning.
Intrusion detection systems (Computer security)
Machine learning
Supervisory control systems
Electronic books.
TJ222
629.8/95583