The study, titled Conditional Adversarial Fragility in Financial Machine Learning under Macroeconomic Stress, published as a ...

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 ...

Artificial intelligence (AI) safety has turned into a constant cat-and-mouse game. As developers add guardrails to block ...

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

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 ...