3 papers
eess.SY2026
Transformer is All You Need: Attention-Based Anomaly Detection and Classification in Inverter-Rich Power Systems
Emad Abukhousa, Saman Zonouz, A. P. Sakis Meliopoulos
Inverter-based resources and IEC 61850 process-bus measurements introduce new protection challenges, including nontraditional fault behavior and measurement-domain cyber-physical a…
eess.SY2026
Latency-Aware Deep Learning Benchmark for Real-Time Cyber-Physical Attack and Fault Classification in Inverter-Dominated Power Grids
Emad Abukhousa, Saman Zonouz, A. P. Sakis Meliopoulos
This work introduces a latency-aware benchmarking framework for evaluating deep learning models in power system anomaly detection using high-fidelity, time-domain signals generated…
eess.SY2025
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning
Emad Abukhousa, Syed Sohail Feroz Syed Afroz, Fahad Alsaeed +3
This paper presents a high-fidelity evaluation framework for machine learning (ML)-based classification of cyber-attacks and physical faults using electromagnetic transient simulat…