Microsoft

Undermining the trust boundary: Investigating a stealthy intrusion through third-party compromise

Microsoft Incident Response investigated an attack operated through legitimate and trusted administrative mechanisms to blend ...
Microsoft

Defending consumer web properties against modern DDoS attacks

Learn how to protect consumer websites and defend against modern DDoS attacks with layered security, resilient architecture, ...
IEEE

An Explainable Hybrid Deep Learning Framework for Network Intrusion Detection Using Feature-Guided CNN Models

Abstract: Cybersecurity risks have evolved in the linked digital terrain of today into more complex, frequent, and varied forms. Conventional intrusion detection systems sometimes find it difficult to ...
Devdiscourse

IoT threat detection moves to transparent, decentralized AI systems

A new study published in Frontiers in Computer Science introduces a decentralized cybersecurity model that combines federated ...
Nature

Fire Detection Systems Using Deep Learning Approaches

The advent of deep learning has transformed fire detection, enabling rapid and accurate identification of flames and smoke across diverse environments. Convolutional neural networks (CNNs) lie at the ...
IEEE

Applying Machine Learning Combined with Dimensionality Reduction to Enhance Intrusion Detection Systems

Abstract: An intrusion detection system (IDS) is a system designed to detect potential intrusion activities, such as malicious activities, computer attacks, or the spread of viruses, and then inform ...
MLB

Everything you need to know about the new ABS Challenge System

At long last, player protest with ball or strike calls can be handled with something other than ineffectual arguing. Beginning with the 2026 MLB season, players will have the power to appeal the ...