By combining accurate anomaly detection with resilience against sophisticated attacks, this XAI-based approach could help safeguard future smart grids, promoting reliable and secure energy ...

In a study published in the journal Information Systems Research, Texas Tech University's Shuo Yu and his collaborators ...

Machine learning (ML) and artificial intelligence (AI) are essential components in modern and effective cybersecurity solutions. However, as the use of ML and AI in cybersecurity is increasingly ...

The dynamic nature of AI-driven ransomware poses significant challenges for detection and defense. Traditional signature-based detection methods are largely ineffective against these adaptive threats.

A mysterious signal, a missing container, and a new breed of threat that strikes and vanishes before tools can react: how a ...

Only machine learning can address the increasing number of challenges in cybersecurity: scaling up security solutions, detecting unknown attacks and detecting advanced attacks, including ...

AI and ML research and technology provider Quantum Ventura will use BrainChip’s Akida technology to develop cyber threat-detection tools.

Why has machine learning become so vital in cybersecurity? This article answers that and explores several challenges that are inherent when applying machine learning.

Human intelligence combined with AI and ML models enable hybrid cybersecurity to better predict, identify and stop security breaches.