Predictive AI Adversarial Input Detection

Detect and block digital or physical adversarial examples submitted to predictive AI models. Adversarial examples are inputs modified or constructed to cause misclassification, missed detection, excessive computation, or another attacker-selected behavior. Apply detection before model inference and monitor for input characteristics or query patterns associated with adversarial example generation, transfer attacks, or black-box optimization. Detection may use statistical tests, auxiliary models, consistency checks, input distribution analysis, or modality-specific adversarial example detectors.