基于抽样流长与完全抽样阈值的异常流自适应抽样算法

doi:10.11999/JEIT141379

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Abstract

The network traffic measurement and anomaly detection for high-speed IP network become the hotspot research of network measurement field. Because the current measurement algorithms have large estimation error for the mice flows and poor performance for the sampling anomaly traffic, an Adaptive Flow sampling algorithm based on the sampled Packets and force sampling Threshold S (AFPT) is proposed. According to the force sampling threshold S, the AFPT is able to sample the mice flows which is sensitive to the anomaly traffic, while adaptive adjustment the probability of sampling based on the sampled packets. The simulation and experimental results show that the estimation error of AFPT is consistent with the theoretical upper bound, and provide better performance for the anomaly traffic sampled. The proposed algorithm can effectively improve the accuracy of anomaly detection algorithm.

Received: 29 October 2014 Published: 02 June 2015

PACS:

TP393

Corresponding Authors: Yi Peng E-mail: qiank126@126.com

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	Yi Peng
	Qian Kun
	Huang Wan-wei
	Wang Jing
	Zhang Zhen

Cite this article:

Yi Peng,Qian Kun,Huang Wan-wei等. Adaptive Flow Sampling Algorithm Based on Sampled Packets and Force Sampling Threshold S Towards Anomaly Detection[J]. JEIT, 2015, 37(7): 1606-1611.

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http://jeit.ie.ac.cn/EN/10.11999/JEIT141379 OR http://jeit.ie.ac.cn/EN/Y2015/V37/I7/1606

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