Authors
Jakapan Suaboot, Adil Fahad, Zahir Tari, John Grundy, Abdun Naser Mahmood, Abdulmohsen Almalawi, Albert Y Zomaya, Khalil Drira
Publication date
2020/4/16
Journal
ACM Computing Surveys (CSUR)
Volume
53
Issue
2
Pages
1-37
Publisher
ACM
Description
Supervisory Control and Data Acquisition (SCADA) systems play an important role in monitoring industrial processes such as electric power distribution, transport systems, water distribution, and wastewater collection systems. Such systems require a particular attention with regards to security aspects, as they deal with critical infrastructures that are crucial to organizations and countries. Protecting SCADA systems from intrusion is a very challenging task because they do not only inherit traditional IT security threats but they also include additional vulnerabilities related to field components (e.g., cyber-physical attacks). Many of the existing intrusion detection techniques rely on supervised learning that consists of algorithms that are first trained with reference inputs to learn specific information, and then tested on unseen inputs for classification purposes. This article surveys supervised learning from a specific security …
Total citations
2020202120222023202431316176
Scholar articles
J Suaboot, A Fahad, Z Tari, J Grundy, AN Mahmood… - ACM Computing Surveys (CSUR), 2020