000			01968cam a22002778i 4500
005			20251223124451.0
008			200618s2021 nju ob 001 0 eng
020			_a9781119606352
020			_a9781119606079
041			_aeng
082	0	0	_a629.8/95583
100	1		_aAlmalawi, Abdulmohsen,
245	1	0	_aSCADA security : _bmachine learning concepts for intrusion detection and prevention / _cAbdulmohsen Almalawi, King Abdulaziz University, Zahir Tari, RMIT University, Adil Fahad, Al Baha University, Xun Yi, Royal Melbourne Institute of Technology.
300			_a1 online resource
490	0		_aWiley series on parallel and distributed computing
520			_a"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"--
650		0	_aSupervisory control systems.
650		0	_aAutomatic control _xSecurity measures.
650		0	_aIntrusion detection systems (Computer security)
650		0	_aMachine learning.
700	1		_aTari, Zahir,
700	1		_aFahad, Adil,
700	1		_aYi, Xun,
856			_uhttps://ieeexplore.ieee.org/servlet/opac?bknumber=9820846
942			_cEBK
999			_c7833 _d7833