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 ...

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 ...

Rivals do not need to break into a server room to steal an artificial intelligence model. A growing body of peer-reviewed ...

In machine learning, privacy risks often emerge from inference-based attacks. Model inversion techniques can reconstruct sensitive training data from model outputs. Membership inference attacks allow ...

The Tidal Cyber 2025 Threat-Led Defense Report represents a groundbreaking shift in cybersecurity analysis by placing real adversary behavior at the forefront of defense strategies. Read the Full ...

Over the past year, I've been working on a challenge that faces every organization implementing Zero Trust: how do you manage thousands of access policies ...