A novel, refined dataset for real-time Network Intrusion Detection
Mikołaj Komisarek, Marek Pawlicki, Maria-Elena Mihăilescu, Darius Mihai, Mihai Carabaș, Rafał Kozik, Michał Choraś · Proceedings of the 17th International Conference on Availability, Reliability and Security · 2022
In this day and age of widespread Internet access, more and more aspects of the economy are becoming dependent on various aspects of network technologies. Cybercrimes are on the rise and massive numbers of network security breaches occur every year. This paper presents network data collected in the Netflow format and its application to detect network attacks. The paper proposes a refined, real-world dataset collected from an academic network. The dataset is a direct result from the experience gained by working on and with the SIMARGL2021 dataset. The applicability of the new dataset is demonstrated on several machine learning algorithms. This novel dataset is open-sourced for researchers to download and use in scientific work.