Detecting cyberattacks in industrial control systems using online learning algorithms

• Main Authors: LI, Guangxia, SHEN, Yulong, ZHAO, Peilin, LU, Xiao, LIU, Jia, LIU, Yangyang, HOI, Steven C. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Online learning; Cost-sensitive learning; Cybersecurity; Industrial control systems; Intrusion detection; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/5132; https://ink.library.smu.edu.sg/context/sis_research/article/6135/viewcontent/Cyberattacks_ICS_algorithms_2019_av.pdf
• Institution: Singapore Management University

Industrial control systems are critical to the operation of industrial facilities, especially for critical infrastructures, such as refineries, power grids, and transportation systems. Similar to other information systems, a significant threat to industrial control systems is the attack from cybersp...