02556oam 2200505 450 991083086960332120210531140740.01-119-60635-71-5231-3709-61-119-60638-11-119-60607-1(CKB)4100000011659102(MiAaPQ)EBC6424081(EXLCZ)99410000001165910220210531d2021 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierSCADA security machine learning concepts for intrusion detection and prevention /Abdulmohsen Almalawi [and three others]Hoboken, New Jersey :John Wiley & Sons, Incorporated,[2021]©20211 online resource (219 pages) illustrations1-119-60603-9 Includes bibliographical references and index."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.Supervisory control systemsAutomatic controlSecurity measuresIntrusion detection systems (Computer security)Supervisory control systems.Automatic controlSecurity measures.Intrusion detection systems (Computer security)629.895583Almalawi Abdulmohsen1689074Tari ZahirFahad AdilYi XunMiAaPQMiAaPQUtOrBLWBOOK9910830869603321SCADA security4063815UNINA