STUDY ON NETWORK INTRUSION DETECTION BASED ON IMPROVED APRIORI ALGORITHM

被引：0
|
作者：
Yang, Nini [1 ]
机构：
[1] Liaoning Shihua Univ, Fushun 113001, Peoples R China
来源：
INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE & TECHNOLOGY, PROCEEDINGS | 2009年
关键词：
Intrusion Detection; Association Ruel; Apriori; Frequent Item-sets; Data Mining;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Association rule mining can effectively improve the performance of intrusion detection system, and generating frequent item-sets is a critical step in association rule mining. Through the research on Apriori algorithm, I propose an algorithm based on set and bit operation for mining frequent item-sets, and use digital view to express the transaction which used each item, use bit operating in digital view to calculate the number of the support of each item-set, and then avoid the problem of repeatedly scanning the database in Apriori algorithm. Experiments show that the algorithm has good performance in network intrusion detection.
引用
收藏
页码：372 / 374
页数：3
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