Daegu Gyeongbuk Institute of Science and Technology (DGIST)
Integrated M.S.-Ph.D. Program, Electrical Engineering and Computer Science
Daegu, South Korea
Advisor: Prof. Donghoon Shin
Curriculum Vitae
Yooshin Kim
Industrial Cybersecurity Researcher
I study how machine learning can improve the security, observability, and resilience of industrial control systems. My recent work focuses on anomaly detection, passive authentication, privacy-preserving analytics, and contextual digital twins for critical infrastructure.
Research Interests
- Anomaly Detection
- Time-Series
- Security & Privacy
- Industrial Control System
- Digital Twin
Education
DGIST
B.S., School of Undergraduate Studies
Daegu, South Korea
University of California, Berkeley
Exchange Student
Berkeley, CA, USA
Research Experience
Digital Twin-Based Fault Diagnosis and Prognosis for Power Plants
Ministry of Science and ICT (MSIT) Daegu, South Korea
- Led development of a drift-aware anomaly detector with dynamic spatio-temporal weighting.
- Built a contextual digital twin using sensor-actuator correlations for anomaly diagnosis.
- Designed a metric to evaluate the utility of time-series anomaly scores.
Cloud-Based Cybersecurity Training Environment for Critical Infrastructure
National Security Research Institute (NSR) Daegu, South Korea
- Led PLC and HMI virtualization using OpenPLC and AdvancedHMI.
- Developed a CODESYS-to-OpenPLC porting tool.
- Designed scenarios and deployed a cloud-based cyber training environment.
ICS Network Visualization System
National Security Research Institute (NSR) Daegu, South Korea
- Led the design and implementation of a Go-based framework for visualizing ICS networks.
Publications
Awards
Preprints and Work in Progress