Harshith Kumar Pedarla explores using GANs to simulate network attacks. Synthetic data augmentation improves detection scores ...

History may soon repeat itself with a novel new platform: networks of AI agents carrying out instructions from prompts and sharing them with other AI agents, which could spread the instructions ...

AI-powered penetration testing is an advanced approach to security testing that uses artificial intelligence, machine learning, and autonomous agents to simulate real-world cyberattacks, identify ...

As the Grammy-winning rocker Beck announced in a recent Instagram post, Everybody's Gotta Learn Sometime is a "lovingly ...

Emerging NIST guidance suggests that the long-standing practice of treating AI as “just software” for cybersecurity purposes ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

Band Power Side-Channel Detection for Semiconductor Supply Chain Integrity at Scale” was published by researchers at Cornell ...

Understanding how threat hunting differs from reactive security provides a deeper understanding of the role, while hinting at how it will evolve in the future.

By Jacob AZAARE Business is the lifeline of every nation, whether state- owned or privately owned. Businesses account for significant part of the economies in both developed and developing countries ...

In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...

A sociotechnical lens highlights red-teaming as a particular arrangement of human labor that unavoidably introduces human value judgments into technical systems, and can pose psychological risks for ...

Adversaries are hijacking AI technology for their own purposes, generating deepfakes, creating clever phishing lures, and launching novel types of advanced attacks. They are also targeting AI systems ...