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Network anomaly detection using nonextensive entropy

delete2007-12-01
delete44
PRE
AI
A
Artur Ziviani
A
Antônio Tadeu A. Gomes
M
Marcelo Monsores
P
Paulo S. Rodrigues
DOI：10.1109/LCOMM.2007.070761delete
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Abstract

Abstract

En 中文
Detection is a crucial step towards efficiently diagnosing network traffic anomalies within an Autonomous System (AS). We propose the adoption of nonextensive entropy - a one-parameter generalization of Shannon entropy - to detect anomalies in network traffic within an AS. Experimental results show that our approach based on nonextensive entropy outperforms previous ones based on classical entropy while providing enhanced flexibility, which is enabled by the possibility of fine-tuning the sensitivity of the detection mechanism.
Keywords:
network anomaly detection

Journal

IEEE Communications Letters cover
IEEE Communications Letters
IF:
4.4
Papers:
1.3W
Citations:
2.2W

Organization

No organization information available