Secure and Resilient Cyber-Physical Systems

点击翻译按钮获取中文摘要

Cyber-physical systems (CPS) are smart systems that include engineered interacting networks of physical and computational components. These integrated systems provide new functionalities to improve quality of life by enabling technological advances in our Critical Infrastructure (CI) such as smart power grids, oil and gas refineries, and smart transportation systems. However, the advancements also lead to new and serious challenges, the primary one being security. Security is a necessary feature of the CIs architecture to ensure that their capabilities are not compromised by malicious activities. The proposed research will develop Artificial Intelligence (AI)-aided tools for intelligent condition monitoring, cyber threat hunting and detection, threat prediction, and threat mitigation to protect Canada's CIs. The focus is on; a) developing intelligent condition monitoring strategies for fault and anomaly detection; b) developing a state-of-the-art multi-view and multi-layer meta-learning enabled model for accurate threat hunting and detection; c) creating a novel stochastic game-theoretic multi-agent reinforcement learning-based attack prediction model to prevent attack propagation and cascading failure in CI; d) developing deep fuzzy learning systems to gather and share cyber threat intelligence for proper attack mitigation and response to cyber-attacks. The research aligns with Canada's Cyber Security Strategy and the National Strategy and Action Plan for CI to build a safer, more secure and more resilient Canada.