apriori算法改进及其在snort ids中的应用分析word格式论文.docxVIP

knowledge and current situation at domestic and international of this research. Chapter two of this paper describes the basic concepts of the Intrusion Detection System, its classification, commonly used detection technology and general system structure, and intruduces the basic concepts of the Data Mining and Knowledge Discovery and some of the major data mining technology, and the application of Data Mining in the IDS. In the chapter three of this paper, we detailed analyze the rule-based and lightweight Intrusion Detection System-Snort and the data mining algorithm-Apriori based on association rules, and made improvements on the Apriori algorithm, then we analysis the effectiveness of the improved Apriori algorithm useing experimental. Chapter four of this paper, we design and implement an Intrusion Detection System based on open source system-Snort, in which we introduced Apriori algorithm that process the data for data mining to find abnormal behavior of network. Through simulation testing and application deployment, we analyze and test the system performance.KeyWords: Intrusion Detection，Data Mining，Association Rules Mining，Snort Intrusion Detection System，Apriori algorithm目录中文摘要 I英文摘要II1 绪论 11.1 研究背景 11.2 国内外研究现状 21.2.1 国外研究现状 21.2.2 国内研究现状 31.3 研究内容 32 入侵检测与数据挖掘技术概述 52.1 入侵检测系统 52.1.1 入侵检测系统概念 52.1.2 入侵检测系统分类 62.1.3 入侵检测系统构成 82.2 数据挖掘技术概述 92.2.1 数据挖掘的基本概念 102.2.2 数据挖掘的分类 112.2.3 主要的数据挖掘技术 122.3 数据挖掘在入侵检测系统中的应用 152.4 本章小结 18Snort IDS 与 Apriori 算法分析193.1 Snort 入侵检测系统 19Snort 系统原理 19Snort 系统部署 28Snort 系统实现 28Snort 系统测试与分析 30Apriori 算法 34Apriori 算法 34Apriori 算法改进 35Apriori 算法分析 373.3 本章小结 404 数据挖掘技术在 Snort IDS 中的应用414.1 应用数据挖掘技术的 Snort IDS 体系结构 414.2 基于 Apriori 算法的异常检测模块 414.2.1 异常检测模块结构 424.2.2 数据预处理 424.2.3 产生频繁项集 434.2.4 生成强关联规则 434.2.5 规则筛选 444.2.6 建立 Snort 规则444.3 系统性能测试与分析 454.4 本章小结 465 工作总结与展望 475.1 总结 475.2 下一步工作的展望 47致谢 49参考文献 50附录 53A. Windows 平台下基于 snort 的入侵检测系统安装与配置53B. Snort 数据库结构56C. 作者在攻读硕士学位期间发表论文的目录571 绪论1.1 研