SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention: SCADA-Based IDs Security by Abdulmohsen Almalawi, Zahir Tari, Adil Fahad, Xun Yi
English | PDF | 2021 | 210 Pages | ISBN : 1119606039 | 5.2 MB
Examines the design and use of Intrusion Detection Systems (IDS) to secure Supervisory Control and Data Acquisition (SCADA) systems
Cyber-attacks on SCADA systems—the control system architecture that uses computers, networked data communications, and graphical user interfaces for high-level process supervisory management—can lead to costly financial consequences or even result in loss of life. Minimizing potential risks and responding to malicious actions requires innovative approaches for monitoring SCADA systems and protecting them from targeted attacks. SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention is designed to help security and networking professionals develop and deploy accurate and effective Intrusion Detection Systems (IDS) for SCADA systems that leverage autonomous machine learning.