关键词: 数据挖掘, 关联规则, Apriori算法, 项集, 入侵检测

Abstract: 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, generating a large number of candidate anthology, and mining frequent itemsets iteratively. This paper presented a method that solved the maximal frequent itemsets through one intersection operation. The degree of support was obtained through the times of intersection without scanning the transaction database. The method was optimized by indexing the attributes so that less memory space is needed and it is easier to search the candidate set list. It generates useful association rules for alerts in Intrusion Detection System (IDS). The experimental results show that the optimized algorithm can effectively improve the efficiency of mining association rules.

Key words: Date Mining, association rules, Apriori algorithm, itemsets, IDS