Aspect | Description |
Gradient-Based Techniques | Leverage model’s gradient to modify inputs for maximizing error in outputs. |
Transferability of Attacks | Adversarial examples for one model often work against different models. |
Autonomous Vehicles | Manipulated data leads to incorrect driving decisions, posing safety risks. |
Security System Breaches | Allow unauthorized access, compromising personal and organizational security. |
Adversarial Training | Training on both regular and adversarial examples to improve model robustness. |
Input Sanitization | Rigorous checks and transformations to detect and mitigate suspicious inputs. |
Regular Model Updates | Continuous updates to recognize new adversarial tactics and patch vulnerabilities. |