1.

Record Nr.

UNINA9910830869603321

Autore

Almalawi Abdulmohsen

Titolo

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

Pubbl/distr/stampa

Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2021]

©2021

ISBN

1-119-60635-7

1-5231-3709-6

1-119-60638-1

1-119-60607-1

Descrizione fisica

1 online resource (219 pages) : illustrations

Disciplina

629.895583

Soggetti

Supervisory control systems

Automatic control - Security measures

Intrusion detection systems (Computer security)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

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"--