Port scan detection algorithms based on statistical traffic features

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Port scan detection algorithms based on statistical traffic features

更新时间：2024-10-14

- Port scan detection algorithms based on statistical traffic features
- Issue 12, Pages: 14-18(2007)
- 作者机构：
  
  1. 西安交通大学机械制造系统工程国家重点实验室
  2. 西安交通大学机械制造系统工程国家重点实验室,陕西,西安,710049
  3. 西安交通大学智能网络与网络安全教育部重点实验室
  4. 清华大学自动化系清华信息科学与技术国家实验室
  5. ,北京,100084
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393.08
- Published：2007
- 稿件说明：
移动端阅览
Port scan detection algorithms based on statistical traffic features[J]. 2007, (12): 14-18.
DOI：

Port scan detection algorithms based on statistical traffic features[J]. 2007, (12): 14-18. DOI：

摘要

根据网络流量的统计特征提出一种慢速端口扫描行为检测算法

以主机数和端口数的比值及被访问主机端口集合之间的相似度为基础

采用非参数累积和CUSUM算法及小波变换方法对流量统计特征进行分析

进而判断是否存在端口扫描行为。实验结果表明

所提取的网络流量特征及算法可以有效地检测异常行为

该方法和Snort相比较具有低的漏报率和误报率。

Abstract

A slowly port scan detect method was presented based on the statistical traffic features.Two statistical features: the ratio between the number of hosts and ports a host communicates and similarities of the ports set

were selected to denote the traffic features.The CUSUM and wavelet transform methods were employed to analyze the features and detect the slowly port scan behaviors.The experimental results show that the methods proposed detect port scan behaviors effi-ciently and correctly

it has low false negative and false positive alarm rate compared with the Snort.

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Related Institution

Department of Operational Operations and Planning, Naval University of Engineering

School of Mathematics and Information Engineering, Xinyang Vocational and Technical College

Department of Information Security, Naval University of Engineering

Network and Information Center, Sun Yat-sen University

Institute of Information Engineering, Chinese Academy of Sciences

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