摘要
结合RSA公钥加密和伪随机数生成器技术,给出一种分布式数据库隐私保护关联规则挖掘算法——PPD-ARBSM。引入密码管理服务器和数据挖掘服务器,能保护敏感数据的安全性,利用事务相似矩阵集中快速实现全局k-项频繁集的生成,能削减各站点间局部支持数对比的通信开销。理论分析与实验结果表明,该算法具有较好的隐私性、准确性和较高的效率。
Combining advantages of the RSA public-key encryption and pseudorandom generator technology, a privacy preserving distributed mining algorithm of association rules, PPD-ARBSM is proposed. It introduces Cryptogram Management Server(CMS) and Data Mining Server (DMS) in the algorithm, PPD-ARBSM effectively protects security of sensitive data, and can make full use of similarity matrix of transactions to generate intensively and quickly global k-frequent itemsets, thus greatly cut down communication costs of contrasting local support between sites. Theoretical analysis and experimental results show that PPD-ARBSM algorithm can achieve improvements in terms of privacy, accuracy, and efficiency.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第17期138-140,共3页
Computer Engineering
基金
广西自然科学基金资助项目(0832264)
广西教育厅基金资助项目(200808MS170)
关键词
RSA公钥加密
隐私保护
数据挖掘
关联规则
分布式数据库
RSA public-key encryption
privacy preservation
data mining
association rule
distributed database