Scada Security: Machine Learning Concepts for Intrusion Detection and Prevention by Almalawi, Abdulmohsen

Scada Security: Machine Learning Concepts for Intrusion Detection and Prevention (Hardcover) (ISBN-13: 9781119606031)

Vendor: Abdulmohsen Almalawi
Product type: Books
Format: Hardcover
$129.95
$129.95
$129.95
Subtotal: $129.95
Scada Security: Machine Learning Concepts for Intrusion Detection and Prevention by Almalawi, Abdulmohsen

Scada Security: Machine Learning Concepts for Intrusion Detection and Prevention

$129.95
Scada Security: Machine Learning Concepts for Intrusion Detection and Prevention by Almalawi, Abdulmohsen

Scada Security: Machine Learning Concepts for Intrusion Detection and Prevention

$129.95
Format: Hardcover
Description
Description
x
"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"--

Author: Abdulmohsen Almalawi, Zahir Tari, Adil Fahad
ISBN-10: 1119606039
ISBN-13: 9781119606031
Publisher: Wiley
Language: English
Published: 12/30/2020
Pages: 224
Format: Hardcover
Weight: 1.05lbs
Size: 9.10h x 6.00w x 0.60d
By Abdulmohsen Almalawi
By Abdulmohsen Almalawi
x

ABDULMOHSEN ALMALAWI, PHD, is Assistant Professor, Department of Computer Science, University of King Abdulaziz, Saudi Arabia. His research is focused on machine learning. He is co-author of Network Classification for Traffic Management.

ZAHIR TARI, PHD, is Professor at RMIT University, Australia. He is on the editorial board of several journals, including ACM Computing Surveys, IEEE Transactions on Computers, IEEE Transactions on Parallel and Distributed Systems, and IEEE Cloud Computing.

ADIL FAHAD, PHD, is Assistant Professor, Department of Computer Science, University of Albaha, Saudi Arabia. His research interests are in the areas of wireless sensor networks, mobile networks, SCADA security, and ad-hoc networks with emphasis on data mining, statistical analysis/modelling, and machine learning.

XUN YI, PHD, is Professor, School of Computer Science and Information Technology, RMIT University, Australia. He has published more than 150 research papers in international journals and has led several Australia Research Council (ARC) Discovery projects. He is Associate Editor of IEEE Transactions on Dependable and Secure Computing.

Recently Viewed Products