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引用次数: 6
摘要
本文重点研究了在保护数据隐私的前提下,对关联规则多方挖掘算法中使用的加密机制进行优化。关注的主要部分集中在提高性能上,因为在应用于大型数据库时,计算费用可能会令人望而却步。介绍了如何在安全集联合中使用公共解密密钥进行交换加密以提高性能。作为上述机制应用的一个实例,本文提出了一种新的水平分区数据关联规则挖掘算法——cdksu (Secure Union with Common Decrypting Key)。CDKSU是安全集合联合中交换加密的公共解密密钥的一种应用。该算法与KCS方案(也称为HPSU)进行了比较,因为它们都是基于FDM的。在性能优化方面,还介绍了椭圆曲线密码与指数密码的应用。我们认为这是椭圆曲线波利-赫尔曼密码应用的第一个描述。描述了实现给定算法的系统,并进行了性能测试。最后,给出了试验结果并进行了分析。
Optimization of Privacy Preserving Mechanisms in Homogeneous Collaborative Association Rules Mining
This article focuses on optimization of cryptographic mechanisms used in association rules multiparty mining algorithms with preserving data privacy. The major part of attention is focused on increasing the performance because the computation expense can be prohibitive when applying to large databases. We introduce how to use a Common Decrypting Key for commutative encryption in Secure Set Union to improve performance. As an example of the above mentioned mechanism application, the article presents a new algorithm of mining association rules on horizontally partitioned data with preserving data privacy-CDKSU (Secure Union with Common Decrypting Key). CDKSU is an application of the Common Decrypting Key for a commutative encryption in a Secure Set Union. This algorithm is compared to the KCS scheme (referenced as HPSU also) since they are both based on FDM. As far as the performance optimization is concerned, the application of Elliptic Curve Cryptography versus Exponential Cryptography is presented as well. We believe that this is the first description of application of the Elliptic Curve Pohlig-Hellman Cipher. The system implementing given algorithms is described and subjected to performance tests. Finally, the results of these tests are presented and analyzed.