山东科学 ›› 2014, Vol. 27 ›› Issue (4): 62-67.doi: 10.3976/j.issn.1002-4026.2014.04.012

• 论文 • 上一篇    下一篇

 基于改进决策树的入侵检测算法

平寒   

  1. 山东职业学院信息工程系,山东 济南 250100
  • 收稿日期:2014-03-03 出版日期:2014-08-20 发布日期:2014-08-20
  • 作者简介:平寒(1980-),女,讲师,研究方向为计算机网络技术与信息安全的教学和研究。Email:yangyun90@163.com

Improved decision tree based intrusion detection algorithm

PING Han   

  1. Department of Information Engineering, Shandong Polytechnic College, Jinan 250100, China
  • Received:2014-03-03 Online:2014-08-20 Published:2014-08-20

摘要:

    本文对经典的基于信息增益的决策树算法进行改进,提出一种基于决策树与属性相关性相结合的入侵检测算法。该算法同时结合综合策略的剪枝算法以避免过度拟合对检测结果的影响。实验结果证明,本算法不仅在面对已知攻击时能够做出良好的判断,而且在面对未知攻击时仍然具有一定的检测能力,具有良好的性能和可用性。

关键词: 信息增益;剪枝算法, 入侵检测, 决策树算法

Abstract:

       This paper improves classical information gain based decision tree algorithm and then presents a decision tree and property relation combined intrusion detection algorithm. The algorithm combines the pruning algorithm of integrated strategy to avoid the impact of excessive fitting on test results. Experimental results show that the algorithm can not only make better judgments when confronting known attacks but also still have certain detection capability when facing unknown attacks. The algorithm thus has better performance and availability.

Key words: pruning algorithm, intrusion detection, decision tree algorithm, information gain

中图分类号: 

  • TP393.08

开放获取 本文遵循知识共享-署名-非商业性4.0国际许可协议(CC BY-NC 4.0),允许第三方对本刊发表的论文自由共享(即在任何媒介以任何形式复制、发行原文)、演绎(即修改、转换或以原文为基础进行创作),必须给出适当的署名,提供指向本文许可协议的链接,同时表明是否对原文作了修改,不得将本文用于商业目的。CC BY-NC 4.0许可协议详情请访问 https://creativecommons.org/licenses/by-nc/4.0