大数据统计划分发布的等比差分隐私预算分配方法  

Proportional Differential Privacy Budget Allocation Method for Partition and Publishing of Statistical Big Data

作　　者：晏燕[1] 张雄 冯涛[1] YAN Yan;ZHANG Xiong;FENG Tao(School of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China)

机构地区：[1]兰州理工大学计算机与通信学院,兰州730050

出　　处：《信息网络安全》2022年第11期24-35,共12页Netinfo Security

基　　金：国家自然科学基金(61762059)。

摘　　要：针对现有的差分隐私大数据统计划分发布方法关于隐私预算分配的问题,文章提出一种等比差分隐私预算分配方法,通过分析大数据统计划分结构和发布误差,推导出等比差分隐私预算分配方法。将文章所提方法与现有其他隐私预算分配方法进行比较,从理论上证明了该方法在各层隐私预算分配和总体误差方面的优势。实验结果表明,文章所提等比差分隐私预算分配方法在范围计数查询精度方面优于其他隐私预算分配方法,有助于提升大数据统计划分发布结果的可用性。In view of the problem of privacy budget allocation method for the existing big data differential privacy statistical partition and publishing,this paper proposed a proportional differential privacy budget allocation method.The hierarchical allocation formula of the proportional privacy budget allocation method was derived through the analysis of the statistical partitioning structure and publishing error of big data.The proposed method was compared with other existing privacy budget allocation methods to prove its advantages theoretically in terms of privacy budget allocation results for each partition layer and the overall publishing error.The experimental results show that the proposed proportional differential privacy budget allocation method has better range counting query accuracy than other existing privacy budget allocation methods,which is helpful to improve the availability of big data statistical partitioning and publishing results.

关 键 词：数据发布隐私保护 隐私空间分解 差分隐私 隐私预算分配 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]