Adversarial machine learning, a technique that attempts to fool models with deceptive data, is a growing threat in the AI and machine learning research community. The most common reason is to cause a ...

To human observers, the following two images are identical. But researchers at Google showed in 2015 that a popular object detection algorithm classified the left image as “panda” and the right one as ...

The final guidance for defending against adversarial machine learning offers specific solutions for different attacks, but warns current mitigation is still developing. NIST Cyber Defense The final ...

“My work protects millions of users, translating theoretical research into practical security implementations at scale.” ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Security leaders’ intentions aren’t matching up with their actions to ...

AI red teaming — the practice of simulating attacks to uncover vulnerabilities in AI systems — is emerging as a vital security strategy. Traditional red teaming focuses on simulating adversarial ...

The National Institute of Standards and Technology (NIST) has published its final report on adversarial machine learning (AML), offering a comprehensive taxonomy and shared terminology to help ...

NIST’s National Cybersecurity Center of Excellence (NCCoE) has released a draft report on machine learning (ML) for public comment. A Taxonomy and Terminology of Adversarial Machine Learning (Draft ...

Artificial intelligence (AI) is transforming our world, but within this broad domain, two distinct technologies often confuse people: machine learning (ML) and generative AI. While both are ...