Latency-Aware Deep Learning Benchmark for Real-Time Cyber-Physical Attack and Fault Classification in Inverter-Dominated Power Grids

In three linesLatency-aware benchmark for 8 deep learning architectures (MLPs, Transformers) in anomaly detection on inverter-dominated power grids. Real-time classification < 15 ms per cycle, but end-to-end latency 50-90 ms (3+ cycles). Critical gap between algorithmic capability and protection-grade deployment identified.

Summary generated by Claude — human-verified