GenAI-FDIA benchmarks physics-informed generative models for stealthy FDIA synthesis on IEEE testbeds, reports high evasion rates, and introduces an inference-time harmoniser plus warm-up schedules to fix projection displacement and covariance collapse.
Sparse adversarial learning for FDIA attack sample generation in distributed smart grids
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GenAI-FDIA: Physics-Informed Generative Models for False Data Injection Attacks
GenAI-FDIA benchmarks physics-informed generative models for stealthy FDIA synthesis on IEEE testbeds, reports high evasion rates, and introduces an inference-time harmoniser plus warm-up schedules to fix projection displacement and covariance collapse.