Network Muscle Learning Project (NML)
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About
The Network Muscle Learning (NML) Project aims to analyze cyber attack trends in real-time using AI/ML technologies, assisting security administrators by predicting potential attacks and their impact. It focuses on processing big data from network devices, servers, social media, and the dark web. The project also aims to establish methods for cyber attack analysis using machine learning and publish the data and methods as open data. Key research outcomes include tools like Deep DNS Filter, Hayabusa, Phish Finder, and SynPicture, each designed to detect and mitigate specific cyber threats.
Platform
Task
Features
• analysis of cyber threat big data
• real-time attack detection and prediction
• incident response decision support system
• synpicture: real-time determination of malicious hosts using syn packet imaging
• phish finder: phishing site identification engine
• hayabusa: scalable high-speed log search engine
• deep dns filter for detecting suspicious software packet processing sites
• open data publication of attack cases
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