From the 1 of 4 linked papers with an AI index.
4 papers
Transformer is All You Need: Attention-Based Anomaly Detection and Classification in Inverter-Rich Power Systems
Emad Abukhousa, Saman Zonouz, A. P. Sakis Meliopoulos
The paper compares an attention‑based Transformer classifier (DL‑Xformer) with a dynamic state estimation method for detecting and classifying faults and measurement‑domain cyber‑p…
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…
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…
Centralized Dynamic State Estimation Algorithm for Detecting and Distinguishing Faults and Cyber Attacks in Power Systems
Emad Abukhousa, Syed Sohail Feroz Syed Afroz, Fahad Alsaeed +2
As power systems evolve with increased integration of renewable energy sources, they become more complex and vulnerable to both cyber and physical threats. This study validates a c…