Adversarial Attack

Sat, 18 Jul 2026 09:45:08 +0000

Definition

Adversarial attacks exploit the vulnerabilities of neural networks by introducing subtle noise to inputs, such as images or text, which causes significant errors in model output. These attacks highlight the fragility of deep learning systems and raise critical safety concerns. They are categorized into white-box attacks, where the attacker has full knowledge of the model, and black-box attacks, where only input-output pairs are observable. Defending against these attacks is essential for deploying robust AI in security-sensitive applications like autonomous driving and facial recognition.

Vulnerability on English AI Terms Dictionary

Adversarial Attack

Definition