基于有损分解的数据隐私保护方法  

A Data Privacy Preservation Method Based on Lossy Decomposition

作　　者：刘玉葆[1] 黄志兰[1] 傅慰慈[2] 印鉴[1] 

机构地区：[1]中山大学计算机科学系,广州510275 [2]香港中文大学计算机科学与工程系

出　　处：《计算机研究与发展》2009年第7期1217-1225,共9页Journal of Computer Research and Development

基　　金：国家自然科学基金项目(60703111;60773198);广东省自然科学基金项目(06104916)~~

摘　　要：隐私保护的数据挖掘近来已成为数据挖掘研究的热点,而数据隐私的保护则是其中的重要问题之一.针对已有方法信息损失程度高、聚集查询精度低的不足,在(alpha,k)隐私保护模型基础上,利用关系数据库理论的有损分解思想,提出了一种改进的数据隐私保护方法Alpha+.该方法首先利用(alpha,k)生成原始数据的匿名数据库,然后,将匿名数据库投影为2个可连接的数据库表NSS和SS,并利用NSS和SS有损连接的冗余信息保护数据隐私.接下来,Alpha+对NSS和SS的元组进行合并,以减少最终发布的数据库表大小.最后比较了Alpha+方法与其他类似方法的安全性.实验结果表明Alpha+在聚集查询精度方面明显优于同类方法.Recently, privacy preserving data mining has been a hot topic in data mining research community. The data privacy preservation is one of the important issues of privacy preserving mining. Many methods have been presented for this problem. However, the existing methods often have the shortcomings of high loss distortion and less aggregate query accuracy on the private or anonymous dataset. In this paper, based on the existing （alpha, k） privacy preservation model, an improved method, Alpha＋, is presented using the lossy decomposition theory of relation database. Alpha＋ firstly use （alpha, k） method to generate the private dataset for the original database. Then the private dataset is projected into two separated tables NSS and SS. The two tables are related with each other through the same relation attributes and then the redundancy information of lossy join of them can be used to preserve the private information. Secondly, Alpha＋ merges the same tuples of NSS and SS tables to reduce the size of them, and the modified NSS and SS are finally published. The security comparison analysis between Alpha＋ and the other similar methods is also given. The experimental results show that Alpha＋ outperforms the existing methods in terms of aggregate query accuracy on the private dataset.

关 键 词：数据隐私保护 隐私保护的数据挖掘 有损分解 K-匿名化 聚集查询 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]