%D 2021
%R 10.1109/ICDABI53623.2021.9655902
%O cited By 6; Conference of 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021 ; Conference Date: 25 October 2021 Through 26 October 2021; Conference Code:176070
%L scholars15439
%J 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021
%X This paper reviews different Industrial Control Systems (ICS) and working mechanisms of Supervisory Control and Data Acquisition (SCADA). To expose the vulnerabilities in the systems, many threat agents are active. Thus, we describe the type of attackers and their motive and different machine learning techniques that may be helpful in detecting those threats that sabotage the whole system. Different machine learning techniques and the suitability of these techniques in different circumstances are described. We gave a critical review of these techniques according to different techniques. Based on these security techniques, we discussed different cybersecurity mechanisms for ICS. We also point out significant challenges that these systems are facing and suggest different precautionary measures that can be taken to nullify these threats. © 2021 IEEE.
%K Intelligent control; Learning algorithms; Machine learning; SCADA systems, Critical review; Cyber security; Industrial control systems; Machine learning techniques; Precautionary measures; Security threats; Supervisory control and data acquisition; Supervisory control and data acquisition.; Threat agents; Working mechanisms, Cybersecurity
%P 630-634
%T Survey on Cyber Security for Industrial Control Systems
%A R.F. Ali
%A A. Muneer
%A P.D.D. Dominic
%A E.A.A. Ghaleb
%A A. Al-Ashmori
%I Institute of Electrical and Electronics Engineers Inc.