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Saturday, October 20 • 2:00pm - 2:30pm
Analytics for Industrial Cyber Control Security

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Modern industrial control systems are highly automated and often controlled by computers and connected devices. In addition to physical failures, cyber attacks present an increasing threat to normal system operations. We propose an unsupervised learning approach for automated detection of adverse cyber attacks. In particular, we will devise the unsupervised learning based approaches for anomaly detection using only datasets collected under normal system conditions. Anomaly detection techniques are extremely useful for real-life system security management because cyber attacks rarely happen in practice even though their impact could be disastrous. We conduct detailed studies on a water treatment plant in which water processes are all connected by computer control systems. We demonstrate our analytics tools can effectively detect new types of cyber attacks and, moreover, can locate potential attacking points and compromised control units or devises

avatar for Honggang Wang

Honggang Wang

Assistant Professor, University of La Verne
Honggang Wang is an assistant professor in Analytics in College of Business and Public Management at University of La Verne. He received his Bachelor of Science degree in Power Engineering from Shanghai Jiao Tong University, Shanghai, China, in 1996, Master of Science in Manufacturing... Read More →

Saturday October 20, 2018 2:00pm - 2:30pm PDT
Ballroom # 409