基于数据挖掘关联规则Apriori改进算法的入侵检测系统的研究

The Research of Intrusion Detection System Based on Improved Apriori Algorithm of Data Mining Association Rules

在众多的关联规则挖掘算法中,Apriori算法是最为经典的一个,但Apriori算法有以下缺陷:需要扫描多次数据库、生成大量候选集以及迭代求解频繁项集。因而提出了一种新方法,使Apriori算法产生的候选项集再通过数据库查找是否为频繁项集,从而提高算法的效率。最后针对入侵检测系统形成关联规则。实验结果表明,改进后的算法能有效地提高关联规则挖掘的效率。

Among a large number of association rule mining algorithms, Apriori algorithm is the most classic one ,but it has three deficiencies,including scanning databases many times, senerating a large number of candidate anthology, and mining frequent itemsets iteratively. This paper presented a method, Apriori algorithm to generate the candidate itemsets and then finds whether it is the frequent item- sets through the database, thereby enhancing the efficiency of the algorithm. Finally, intrusion detection system for the formation of association rules （IDS）. The experimental results show that the optimized algorithm can effectively improve the efficiency of mining association rules.