Adaptive algorithms for identifying large flows in IP traffic

Abstract : We propose in this paper an on-line algorithm based on Bloom filters for identifying large flows in IP traffic (a.k.a. elephants). Because of the large number of small flows, hash tables of these algorithms have to be regularly refreshed. Recognizing that the periodic erasure scheme usually used in the technical literature turns out to be quite inefficient when using real traffic traces over a long period of time, we introduce a simple adaptive scheme that closely follows the variations of traffic. When tested against real traffic traces, the proposed on-line algorithm performs well in the sense that the detection ratio of long flows by the algorithm over a long time period is quite high. Beyond the identification of elephants, this same class of algorithms is applied to the closely related problem of detection of anomalies in IP traffic, e.g., SYN flood due for instance to attacks. An algorithm for detecting SYN and volume flood anomalies in Internet traffic is designed. Experiments show that an anomaly is detected in less than one minute and the targeted destinations are identified at the same time.
Document type :
Preprints, Working Papers, ...
Complete list of metadatas

Cited literature [20 references]  Display  Hide  Download

https://hal.inria.fr/inria-00357343
Contributor : Philippe Robert <>
Submitted on : Saturday, June 20, 2009 - 11:14:16 AM
Last modification on : Friday, May 25, 2018 - 12:02:03 PM
Long-term archiving on : Saturday, November 26, 2016 - 10:11:16 AM

Files

Hal.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00357343, version 2
  • ARXIV : 0901.4846

Collections

Citation

Youssef Azzana, Yousra Chabchoub, Christine Fricker, Fabrice Guillemin, Philippe Robert. Adaptive algorithms for identifying large flows in IP traffic. 2009. ⟨inria-00357343v2⟩

Share

Metrics

Record views

234

Files downloads

712