The 2025 SANS SOC Survey shows AI use is rising, but many SOCs lack integration, customization, and clear validation ...

Artificial intelligence (AI) and machine learning (ML) are predicted to have a significant impact on future industrial ...

That’s the aim of predictive cyber resilience (PCR)—an emerging approach to security built on intelligence, automation and ...

This project implements an Intrusion Detection System using machine learning algorithms to detect malicious network activities. It analyzes network traffic patterns, packet headers, and flow data to ...

Distributed Cyber-Immune Mesh for Legacy Infrastructure Protection Using Adaptive AI Sentinels Note: This README is an ultra-condensed summary of the research reports published by Unpatentable.org. To ...

PARIS (AP) — The head of the Louvre Museum said Wednesday that new surveillance cameras and anti-intrusion systems will soon be installed at the Paris landmark after last month’s stunning crown jewels ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

Abstract: Distributed Intrusion Detection Systems (DIDS) in resource-constrained edge environments have become increasingly important due to the development of the Industrial Internet of Things (IIoT) ...

What if technology could bridge the gap between spoken language and sign language, empowering millions of people to communicate more seamlessly? With advancements in deep learning, this vision is no ...