Sada klasifikačních modulů pro detekci bezpečnostních hrozeb

The collection of classification modules detecting security threats

software

optional - optional free

Plný Richard (FIT CTU)
Luxemburk Jan (CESNET)
Hynek Karel, Ing. (CESNET)
Čejka Tomáš, doc. Ing., Ph.D. (FIT CTU)
Šiška Pavel, Bc. (CESNET)
Koumar Josef (FIT CTU)
Jeřábek Kamil, Ing., Ph.D. (DIFS FIT BUT)

Classification, machine learning, encrypted traffic, security threats

This software presents production-ready encrypted traffic classifiers, that are using machine learning. The goal is to significantly improve the ability to classify encrypted network traffic, which is key to identifying security threats and increasing network situational awareness. The use of modern machine learning technologies brings new perspectives and effective tools for securing information systems against complex cyber threats. The designed software solution has the potential to improve the ability of organizations to identify and solve security incidents in real time.

https://gitlab.liberouter.org/monitoring/feta-v3

Flow-based Encrypted Traffic Analysis (VJ02010024)

NES@FIT - Networks and distributed systems research group (VZ NES@FIT)

CESNET National Research and Education Network (CESNET)
Faculty of Information Technology BUT (FIT BUT)
Faculty of Information Technology, Czech Technical University (FIT CTU)