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 ...

AI didn't just create new attack surfaces. It fundamentally changed who—and what—is requesting access in your environment. Zero Trust needs an upgrade for a world where autonomous agents outnumber ...

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 ...

Adam Stone writes on technology trends from Annapolis, Md., with a focus on government IT, military and first-responder technologies. Cybercriminal groups are leveraging artificial intelligence to ...

The White House, in its “Cyber Strategy for America” released on the 6th, declared its intent to maintain U.S. dominance in emerging technologies such as artificial intelligence (AI) and quantum ...

When an engineer discovers that an AI system has generated a fabricated attack piece targeting them personally, the incident stops being theoretical and becomes an urgent warning about how adversarial ...

Faced with increasingly sophisticated multi-domain attacks slipping through due to alert fatigue, high turnover and outdated tools, security leaders are embracing AI-native security operations centers ...

A bipartisan group of U.S. lawmakers introduced the No Adversarial AI Act on Wednesday in an effort to ban Chinese artificial intelligence models, such as those made by DeepSeek (DEEPSEEK), in federal ...

In this photo illustration, the DeepSeek app is displayed on an iPhone screen on Jan. 27, 2025 in San Anselmo, Calif. (Photo Illustration by Justin Sullivan/Getty Images) Federal agencies would be ...

CrowdStrike's 2026 report finds 82% of attacks are malware-free, breakout times average 29 minutes, and adversaries exploit trust in identities, cloud, and supply chains.

IFAP generates adversarial perturbations using model gradients and then shapes them in the discrete cosine transform (DCT) domain. Unlike existing frequency-aware methods that apply a fixed frequency ...