Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in image-related tasks. These systems have found applications in medical diagnosis, ...

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 ...

Autonomous SOC agents now shipping can rewrite firewall rules and modify IAM policies — outpacing the governance frameworks ...

SAN FRANCISCO, March 19, 2026 (GLOBE NEWSWIRE) -- Votal AI, the AI-native security platform purpose-built for agentic AI systems and founded by cybersecurity veterans Bobby Gupta (CEO) and Jyotirmoy ...

From data poisoning to prompt injection, threats against enterprise AI applications and foundations are beginning to move from theory to reality. Attacks against AI systems and infrastructure are ...

Effective AI defense requires treating AI systems as lifecycle assets with multiple protection layers. A resilient ...

All the narratives about artificial intelligence seem to be centered around "doing more" with not as much consideration given to AI security. In fact, in a recent survey, over one-third of enterprise ...

In today’s digital landscape, cyber threats are evolving at an unprecedented pace. Traditional security measures struggle to ...

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 ...