一种新的保护隐私的关联规则挖掘技术

R. S. Mohammed, Enas Mohammed Hussien, Jinan Redha Mutter
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引用次数: 6

摘要

保护隐私的关联规则挖掘(PPAM)近年来成为一个重要的研究课题。由于数据挖掘本身不足以在没有隐私保护的情况下在公司之间共享数据。本文提出了一种利用随机标准映射构造关联规则来保证数据机密性的新技术,而无需重新挖掘敏感数据。利用Matlab对系统进行了仿真并进行了测试,结果表明系统的原始数据与制作的数据相差很大。并且还实现了高速度和更少的内存要求。
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A novel technique of privacy preserving association rule mining
Privacy Preserving Association Rule Mining (PPAM) becomes an important issue in recent years. Since data mining alone is not enough to share data between companies without privacy preserving. In this paper, a new technique has been proposed to maintain the confidentiality of the data by fabricating of association rule using a stochastic standard map without returning to mining sensitive data again. The system simulation using Matlab and tested that shows the successful difference between the original data and fabricated. And also been achieved high speed and fewer memory requirements.
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