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.