To explore LLMs' effectiveness in detecting network threats, researchers emulated a wireless communication environment using ...

However, medical digital twins are susceptible to adversarial attacks, where small, intentional modifications to input data ...

Your dashboards say you're secure—but 41% of threats still get through. Picus Security's Adversarial Exposure Validation ...

But these models face significant threat from adversarial attacks, which can derail predictions and produce incorrect ...

Medical digital twins are virtual models of the human body that can help predict diseases with high accuracy. However, they ...

It is designed to aid in securing AI applications against attacks that include adversarial manipulation of training data, ...

AI and machine learning algorithms have fast-tracked automation in South Africa’s insurance industry, but these solutions also introduce unique cybersecurity vulnerabilities.

Limited Scope: The testing scope is often focused on specific scenarios or pre-defined attack paths, missing broader risks and emerging threats. • Lack Of Real-World Adversarial Emulation ...

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 ...