[1]杨德璋 李雷 申方成.快速多规则约束关联算法的入侵检测研究[J].计算机技术与发展,2010,(12):173-176.
　YANG De-zhang,LI Lei,SHEN Fang-cheng.Intrusion Detection Technology Research Based on Fast Multi-association Mining Algorithm[J].,2010,(12):173-176.
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快速多规则约束关联算法的入侵检测研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2010年12期
页码:
173-176
栏目:
安全与防范
出版日期:
1900-01-01

文章信息/Info

Title:
Intrusion Detection Technology Research Based on Fast Multi-association Mining Algorithm
文章编号:
1673-629X（2010）12-0173-04
作者:
杨德璋1 李雷1 申方成2
[1]南京邮电大学自动化学院[2]南京邮电大学数理学院
Author(s):
YANG De-zhang; LI Lei; SHEN Fang-cheng
[1]School of Automation,Nanjing University of Posts and Telecommunications[2]School of Mathematics ＆ Physics,Nanjing University of Posts and Telecommunications
关键词:
入侵检测; 数据挖掘; 关联规则; 频繁项集; 模糊C均值聚类算法; 规则约束
Keywords:
intrusion detection;  data mining;  association rules;  frequent itemsets;  fuzzy C-means clustering algorithm;  rule constraint
分类号:
TP393.08
文献标志码:
A
摘要:
入侵特征值识别和发现算法是误用入侵检测中的关键技术。针对数据挖掘经典的Apriori算法中多次扫描事务数据库而产生很大I/O负载和可能产生庞大的无用候选集的问题,提出了一种基于快速多规则约束Apriori算法。算法实时更新了入侵检测系统的规则库,提高了整个系统的检测性能,有效降低虚警率和误报率。同时考虑到强规则事件并不一定是有趣事件的问题,算法加入递减支持度约束。试验结果显示,该算法相比Apriori算法在系统的入侵检测效率上有很好的改善
Abstract:
Invasion eigenvalue and discovery algorithm are the key technologies to misuse intrusion detection technology.To solve Apriori algorithm＇s two problems： one is that scanning the transaction database repeatedly produce large I/O load;the other is that it may have unwanted large candidate sets.Presents a fast multi-constrained Apriori algorithm,which can real-time update of intrusion detection system rule-base,improve detection performance of the entire system,effectively reduce the false alarm rate and false alarm rate.Considering that the current new attacks are derivatives of old existing attacks,many of them have same characteristics of sub-strings,and not every events with strong rules are fun events,the new algorithm adds the decreasing support constraints.Experiment results indicate that the proposed method is efficient

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备注/Memo

备注/Memo:
国家自然科学基金项目（10371106 10471114）; 江苏省高校自然科学基金项目（04KJB110097 08KJB520023）; 南京邮电大学攀登计划项目（NY207064）杨德璋（1984-），男，硕士研究生，研究方向为数据挖掘与计算智能；李雷，教授，研究方向为智能信号处理、非线性分析与计算智能
更新日期/Last Update: 1900-01-01