CAJ | 학술논문

针对垂直分布下的隐私保护关联规则挖掘算法效率低、安全性不高的问题,提出一种隐私保护频繁闭合项集的挖掘算法。算法利用挖掘频繁闭合项集代替频繁项集,IT-Tree作为搜索空间,Diffsets作为压缩结构,采用基于 RSA可交换加密算法的隐私保护集合差集协议。实验结果表明,算法具有较好的隐私性、准确性、高效性。
침대수직분포하적은사보호관련규칙알굴산법효솔저、안전성불고적문제,제출일충은사보호빈번폐합항집적알굴산법。산법이용알굴빈번폐합항집대체빈번항집,IT-Tree작위수색공간,Diffsets작위압축결구,채용기우 RSA가교환가밀산법적은사보호집합차집협의。실험결과표명,산법구유교호적은사성、준학성、고효성。
The existing privacy preserving association rule mining algorithms in vertically partitioned data is lower efficient and unsafe,so a new privacy protection algorithm for mining frequent closed itemsets is proposed.The algorithm generates frequent closed itemsets instead of frequent itemsets with IT-Tree as the search space and Diffsets as a compressed struc-ture.The algorithm uses the difference set of privacy preserving protocol based on exchangeable RSA encryption.Theoreti-cal analysis and experimental results show that the algorithm improves security,accuracy and efficiency.