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.

SeriesWiley series on parallel and distributed computing
Abstract "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.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Source of descriptionDescription based on print version record and CIP data provided by publisher; resource not viewed.
Issued in other formPrint version: Almalawi, Abdulmohsen. SCADA security Hoboken, NJ, USA : Wiley, 2021. 9781119606031
Genre/formElectronic books.
LCCN 2020027877
ISBN9781119606352 (epub)
ISBN9781119606079 (adobe pdf)
ISBN(cloth)

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