基于模糊理论与关联规则的入侵检测模型

章坚武; 黄佳森; 周迪

doi:10.11959/j.issn.1000-0801.2019077

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基于模糊理论与关联规则的入侵检测模型

研究与开发 | 更新时间：2024-06-05

- 基于模糊理论与关联规则的入侵检测模型
- Intrusion detection model based on fuzzy theory and association rules
- 电信科学 2019年35卷第5期页码：59-69
- 作者机构：
  
  1. 杭州电子科技大学，浙江杭州 310018
  2. 浙江宇视科技有限公司，浙江杭州 310018
- 作者简介：
  
  [ "章坚武（1961- ），男，杭州电子科技大学通信工程学院教授、博士生导师，主要研究方向为移动互联网、多媒体通信技术、网络安全等。" ]
  [ "黄佳森（1992- ），男，杭州电子科技大学通信工程学院硕士生，主要研究方向为数据挖掘、网络安全等。" ]
  [ "周迪（1975- ），男，浙江宇视科技有限公司高级工程师、宇视研究院院长，主要研究方向为视频安全、人工智能等。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61772162);国家自然科学基金资助项目;The National Natural Science Foundation of China(U1866209);国家重点研发计划经费资助项目;The National Key Research Development Program of China(2016YFB0800201);浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Province of China(LY16F020016)
- DOI：10.11959/j.issn.1000-0801.2019077
  中图分类号： TP393
- 网络出版日期：2019-05，
  
  纸质出版日期：2019-05-20
- 稿件说明：
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章坚武, 黄佳森, 周迪. 基于模糊理论与关联规则的入侵检测模型[J]. 电信科学, 2019,35(5):59-69.

Jianwu ZHANG, Jiasen HUANG, Di ZHOU. Intrusion detection model based on fuzzy theory and association rules[J]. Telecommunications science, 2019, 35(5): 59-69.
章坚武, 黄佳森, 周迪. 基于模糊理论与关联规则的入侵检测模型[J]. 电信科学, 2019,35(5):59-69. DOI： 10.11959/j.issn.1000-0801.2019077.

Jianwu ZHANG, Jiasen HUANG, Di ZHOU. Intrusion detection model based on fuzzy theory and association rules[J]. Telecommunications science, 2019, 35(5): 59-69. DOI： 10.11959/j.issn.1000-0801.2019077.

摘要

利用 BV-Apriori 算法生成匹配规则库，引入模糊集合技术解决连续型数据划分过程中边界过硬的问题，完成特征之间关系的实时分析与规则库的更新，搭建入侵检测BVA-IDS（Boolean vector Apriori-intrusion detection system）模型。研究结果表明，相比顺序生成频繁项集的Apriori算法与已有文献的Apriori-BR算法，本文的BV-Apriori算法挖掘效率显著地提高；相比已有文献的检测模型，本文的BVA-IDS模型在入侵检测指标上表现较好，有较高的检测准确性与较低的误检率和漏检率。

Abstract

An intrusion detection model based on fuzzy theory and improved Apriori algorithm was proposed.The BV-Apriori algorithm was used to generate the matching rule base

and the problem of excessive boundary in the continuous data partitioning process was solved by fuzzy set technology.The real-time analysis of the relationship between features and the update of the rule base were completed

and the intrusion detection model BVA-IDS (Boolean vector Apriori-intrusion detection system) was built.The results show that the mining efficiency of the BV-Apriori algorithm is significantly improved when compared with the existing Apriori-BR algorithm

in addition

the BVA-IDS model also performs well on intrusion detection indicators with high detection accuracy

and low false positive rate and false negative rate.

关键词

Keywords

references

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