Tech Xplore

Two animal-inspired algorithms just changed how software-defined networks catch attacks before disruptions spread

Researchers have developed a new artificial intelligence-based system designed to improve cyberattack detection in ...
Morning Overview on MSN

Sysdig just documented the first AI agent that ran a full cyber intrusion start to finish — four pivots and a database drained in under an hour with no human at the keybo…

Sysdig reported what it describes as the first fully autonomous AI agent to execute a complete cyber intrusion, from initial ...
IEEE

A Novel Contrastive Loss for Zero-Day Network Intrusion Detection

Abstract: Machine learning has achieved state-of-the-art results in network intrusion detection; however, its performance significantly degrades when confronted by a new attack class— a zero-day ...
Devdiscourse

AI, zero trust and threat hunting shape next phase of global cybersecurity defense

Read more about AI, zero trust and threat hunting shape next phase of global cybersecurity defense on Devdiscourse ...
Scientific Research Publishing

Ferrag, M.A., Maglaras, L., Moschoyiannis, S. and Janicke, H. (2020) Deep Learning for Cyber Security Intrusion Detection: Approaches, Datasets, and Comparative Study. Journal ...

ABSTRACT: The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior using deep learning methods and ensuring interpretability of ...
IEEE

Machine learning-based intrusion detection and prevention using cross-layer features in Internet of Things (IoT) networks

Abstract: The IoT has emerged as a significant target for cyber-attacks, particularly with a focus on the routing protocol for low-power and lossy networks (RPL) within Wireless Sensor Networks (WSNs) ...