SCADA security : machine learning concepts for intrusion detection and prevention / / Abdulmohsen Almalawi [and three others]

• Autore: Almalawi Abdulmohsen
• Pubblicazione: Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2021]; ©2021
• Descrizione fisica: 1 online resource (219 pages) : illustrations
• Disciplina: 629.895583
• Soggetto topico: Supervisory control systems; Automatic control - Security measures; Intrusion detection systems (Computer security)
• Persona (resp. second.): TariZahir; FahadAdil; YiXun
• Nota di bibliografia: Includes bibliographical references and index.
• Sommario/riassunto: "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"--
• Titolo autorizzato: SCADA security
• ISBN: 1-119-60635-7; 1-5231-3709-6; 1-119-60638-1; 1-119-60607-1
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910830869603321
• Lo trovi qui: Univ. Federico II