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Measuring the Histogram Feature Vector for Anomaly Network Traffic

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 3802)

Abstract

Recent works have shown that Internet traffics are self- similar over several time scales from microseconds to minutes. On the other hand, the dramatic expansion of Internet applications give rise to a fundamental challenge to the network security. This paper presents a statistical analysis of the Internet traffic Histogram Feature Vector, which can be applied to detect the traffic anomalies. Besides, the Variant Packet Sending-interval Link Padding based on heavy-tail distribution is proposed to defend the traffic analysis attacks in the low or medium speed anonymity system.

Keywords

Pareto Distribution Link Group Constant Length Tail Index Heavy Tail Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Wei Yan
    • 1
  1. 1.McAfee Inc 

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