Continual Adversarial Reinforcement Learning (CARL) of False Data
Injection detection: forgetting and explainability
Continual Adversarial Reinforcement Learning (CARL) of False Data
Injection detection: forgetting and explainability
False data injection attacks (FDIAs) on smart inverters are a growing concern linked to increased renewable energy production. While data-based FDIA detection methods are also actively developed, we show that they remain vulnerable to impactful and stealthy adversarial examples that can be crafted using Reinforcement Learning (RL). We propose to …