Mining NetFlow Records for Critical Network Activities - Mechanisms for Autonomous Management of Networks and Services Access content directly
Conference Papers Year : 2010

Mining NetFlow Records for Critical Network Activities

Abstract

Current monitoring of IP flow records is challenged by the required analysis of large volume of flow records. Finding essential information is equivalent to searching for a needle in a haystack. This analysis can reach from simple counting of basic flow level statistics to complex data mining techniques. Some key target objectives are for instance the identification of malicious traffic as well as tracking the cause of observed flow related events. This paper investigates the usage of link analysis based methods for ranking IP flow records. We leverage the well known HITS algorithm in the context of flow level dependency graphs. We assume a simple dependency model that can be build in the context of large scale IP flow record data. We apply our approach on several datasets, ranging from ISP captured flow records up to forensic packet captures from a real world intrusion.
Fichier principal
Vignette du fichier
61550135.pdf (571.66 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01056635 , version 1 (20-08-2014)

Licence

Attribution

Identifiers

Cite

Shaonan Wang, Radu State, Mohamed Ourdane, Thomas Engel. Mining NetFlow Records for Critical Network Activities. 4th International Conference on Autonomous Infrastructure, Management and Security (AIMS), Jun 2010, Zurich, Switzerland. pp.135-146, ⟨10.1007/978-3-642-13986-4_20⟩. ⟨hal-01056635⟩
120 View
191 Download

Altmetric

Share

Gmail Facebook X LinkedIn More