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 ...

As AI applications and capabilities continue to progress rapidly, so do efforts into exploiting its vulnerabilities, mainly through the Adversarial AI research field. As these trends persist, AI ...

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 ...

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 ...

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

A five-year “adversarial collaboration” of consciousness theorists led to a stagy showdown in front of an audience. It crowned no winners — but it can still claim progress. Science routinely puts ...