Intrusion detection method based on hierarchical hidden Markov model and variable-length semantic pattern

DUAN Xue-tao1; JIA Chun-fu 1; LIU Chun-bo1

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Intrusion detection method based on hierarchical hidden Markov model and variable-length semantic pattern

更新时间：2024-10-14

- Intrusion detection method based on hierarchical hidden Markov model and variable-length semantic pattern
- Vol. 31, Issue 3, Pages: 109-114(2010)
- 作者机构：
  
  1. 南开大学信息技术科学学院
  2. 国家计算机病毒应急处理中心
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393.08
- Published：2010
- 稿件说明：
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DUAN Xue-tao1, JIA Chun-fu 1, LIU Chun-bo1. Intrusion detection method based on hierarchical hidden Markov model and variable-length semantic pattern[J]. 2010, 31(3): 109-114.
DOI：

DUAN Xue-tao1, JIA Chun-fu 1, LIU Chun-bo1. Intrusion detection method based on hierarchical hidden Markov model and variable-length semantic pattern[J]. 2010, 31(3): 109-114. DOI：

摘要

分析了定长系统调用短序列在入侵检测系统应用中的不足

利用进程堆栈中的函数调用返回地址信息

提出了一种变长短序列的语义模式切分方法

并根据这种变长语义模式之间的层次关系和状态转移特性提出了基于层次隐马尔科夫模型的入侵检测方法。实验结果表明

与传统的隐马尔科夫模型相比

基于层次隐马尔科夫模型的入侵检测方法具有更好的检测效果。

Abstract

The defects of intrusion detection using fixed-length short system call sequences were analyzed. A method of extracting variable-length short system call sequences

grounded on the function return addresses stored in the process stacks

was proposed. Based on the hierarchical relationship and the state transition characteristics of the variable-length semantic patterns

a hierarchical hidden Markov intrusion detection model was presented. The experimental results show that the hierarchical hidden Markov intrusion detection model is superior to the traditional hidden Markov model.

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