Cyber threats are increasing in speed and complexity, driving the need for advanced detection techniques. Machine learning is ...

From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This evolution unites physical and cyber domains, improves situational awareness, and ...

In today's rapidly evolving digital landscape, the convergence of artificial intelligence (AI), machine learning, and cloud-based solutions is reshaping the foundation of security practices. These ...

In today’s rapidly evolving AI landscape, ensuring the security and integrity of machine learning models has never been more important.

Artificial intelligence and machine learning projects require a lot of complex data, which presents a unique cybersecurity risk. Security experts are not always included in the algorithm development ...

Sivan Tehila, CEO & Founder of Onyxia Cyber and Cybersecurity Masters Program Director at the YU Katz School of Science and Health. For years, cybersecurity has been reactive in practice—with ...

Apple has shared recordings of talks from its workshop about privacy and machine learning, demonstrating how it is considering how to protect user data while it is processed using AI. Apple has ...

A new report out today from software supply chain company JFrog Ltd. reveals a surge in security vulnerabilities in machine learning platforms, highlighting the relative immaturity of the field ...

A new study published in Engineering presents a novel framework that combines machine learning (ML) and blockchain technology (BT) to enhance computational security in engineering. The framework, ...

Set in National Harbor, Maryland, this two-day forum by Defense Strategies Institute is centered on the operational and ...