Adversarial Attack

In more detail

Small, carefully crafted input changes can fool even accurate models. Impacts classification confidence and predictions. Defenses include adversarial training, input validation, and detection methods. Important for model robustness.

Examples

• Adding imperceptible noise to images
• Misclassifying stop signs
• Fake audio for speech recognition
• Text perturbations for NLP