Xiao-Fang Ji

Papers

Total Citations

H-Index

About

Dr. Xiao-Fang Ji is a leading researcher in the security of industrial control systems (ICS), with a focus on developing dynamic, data-driven frameworks to counter emerging cyber threats. Her most-cited work introduces a three-stage dynamic assessment framework that leverages a Weighted Hidden Markov Model (W-HMM) to evaluate and predict security risks in ICS environments. This contribution is particularly significant as it addresses the growing vulnerabilities introduced by cloud computing, artificial intelligence, and big data analytics—technologies that, while transformative, have expanded the attack surface for critical infrastructure. By modeling the temporal and probabilistic nature of cyberattacks, Dr. Ji’s framework enables more adaptive and proactive risk management, helping organizations safeguard corporate capital and operational continuity. Her research bridges the gap between theoretical modeling and practical industrial application, earning her recognition among peers and practitioners. With a citation count reflecting the relevance of her work in a rapidly evolving field, Dr. Ji continues to advance the resilience of industrial systems against sophisticated cyber threats, making her a key voice in the intersection of cybersecurity and critical infrastructure protection.