基于过抽样技术的P2P流量识别方法

钱亚冠; 张旻

doi:10.3969/j.issn.1000-0801.2014.04.016

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基于过抽样技术的P2P流量识别方法

研究与开发 | 更新时间：2024-06-05

- 基于过抽样技术的P2P流量识别方法
- P2P Traffic Identification Based Over-Sampling Technique
- 电信科学 2014年30卷第4期页码：109-113
- 作者机构：
  
  1. 浙江科技学院理学院杭州 310023
  2. 杭州电子科技大学计算机学院杭州 310018
- 作者简介：
  
  [ "钱亚冠，男，博士，浙江科技学院理学院副教授，主要研究方向为互联网流量分类、下一代互联网、机器学习与数据挖掘。" ]
  [ "张旻，男，博士，杭州电子科技大学计算机学院讲师，主要研究方向为网络虚拟化、下一代互联网、软件定义网络。" ]
- 基金信息：
  
  浙江省网络媒体云处理与分析工程技术中心开放课题资助项目;Education Department Foundation of Zhejiang Province(2012E10023-14)
- DOI：10.3969/j.issn.1000-0801.2014.04.016
  中图分类号：
- 网络出版日期：2014-04，
  
  纸质出版日期：2014-04-20
- 稿件说明：
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钱亚冠, 张旻. 基于过抽样技术的P2P流量识别方法[J]. 电信科学, 2014,30(4):109-113.

Yaguan Qian, Min Zhang. P2P Traffic Identification Based Over-Sampling Technique[J]. Telecommunications science, 2014, 30(4): 109-113.
钱亚冠, 张旻. 基于过抽样技术的P2P流量识别方法[J]. 电信科学, 2014,30(4):109-113. DOI： 10.3969/j.issn.1000-0801.2014.04.016.

Yaguan Qian, Min Zhang. P2P Traffic Identification Based Over-Sampling Technique[J]. Telecommunications science, 2014, 30(4): 109-113. DOI： 10.3969/j.issn.1000-0801.2014.04.016.

摘要

针对P2P类不平衡问题提出将复杂的多类不平衡问题转化为简单的两类不平衡问题，再通过迭代SMOTE过抽样技术丰富P2P的概念表达，从而提高P2P流量的识别率。实验结果表明，该方法可以显著提高诸如Naïve Bayes这样的简单模型在P2P上的识别率，由此可证明该方法对于改善P2P类不平衡问题的有效性。

Abstract

A new approach that transfers the multi-class imbalanced problem into simple two-class imbalanced problem was proposed

and a mended SMOTE over-sampling algorithm to enrich the P2P concept was applied. The experimental results show the approach can efficiently improve the P2P identifying rate using the Naïve Bayes model.

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references

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