Adversarial AI exploits model vulnerabilities by subtly altering inputs (like images or code) to trick AI systems into misclassifying or misbehaving. These attacks often evade detection because they ...

For decades, cybersecurity relied heavily on signature-based detection and static rule systems. These tools were effective ...

Artificial Intelligence (AI) has become a buzzword in today’s tech-driven world, promising new possibilities and reshaping industries. Despite its prevalence, ...

In the research, they analyze the relation of adversarial transferability and output consistency of different models, and observe that higher output inconsistency tends to induce lower transferability ...

We’ve touched previously on the concept of adversarial examples—the class of tiny changes that, when fed into a deep-learning model, cause it to misbehave. In March, we covered UC Berkeley professor ...