Sada klasifikačních modulů pro detekci bezpečnostních hrozeb

The collection of classification modules detecting security threats

software

Use of the result by another entity is possible without acquiring a license in some cases

The licensor does not require a license fee for the result in some cases

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

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, MV, Strategická podpora rozvoje bezpečnostního výzkumu ČR 2019–2025 (IMPAKT 1) PODPROGRAMU 1 SPOLEČNÉ VÝZKUMNÉ PROJEKTY (BV IMP1/2VS), VJ02010024, 2022-2025, running

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

Faculty of Information Technology (FIT)