Skip to Main content Skip to Navigation
Conference papers

Making Flow-Based Security Detection Parallel

Marek Švepeš 1 Tomáš Čejka 2 
2 CESNET [Prague]
CAS - Czech Academy of Sciences [Prague]
Abstract : Flow based monitoring is currently a standard approach suitable for large networks of ISP size. The main advantage of flow processing is a smaller amount of data due to aggregation. There are many reasons (such as huge volume of transferred data, attacks represented by many flow records) to develop scalable systems that can process flow data in parallel. This paper deals with splitting a stream of flow data in order to perform parallel anomaly detection on distributed computational nodes. Flow data distribution is focused not only on uniformity but mainly on successful detection. The results of an experimental analysis show that the proposed approach does not break important semantic relations between individual flow records and therefore it preserves detection results. All experiments were performed using real data traces from Czech National Education and Research Network.
Complete list of metadata

Cited literature [13 references]  Display  Hide  Download
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Friday, June 1, 2018 - 4:01:15 PM
Last modification on : Tuesday, January 19, 2021 - 10:16:03 AM
Long-term archiving on: : Sunday, September 2, 2018 - 4:41:48 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



Marek Švepeš, Tomáš Čejka. Making Flow-Based Security Detection Parallel. 11th IFIP International Conference on Autonomous Infrastructure, Management and Security (AIMS), Jul 2017, Zurich, Switzerland. pp.3-15, ⟨10.1007/978-3-319-60774-0_1⟩. ⟨hal-01806062⟩



Record views


Files downloads