首页> 外文会议>Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy >Bloom Filter Bootstrap: Privacy-Preserving Estimation of the Size of an Intersection
【24h】

Bloom Filter Bootstrap: Privacy-Preserving Estimation of the Size of an Intersection

机译:Bloom Filter Bootstrap:保留交叉点大小的隐私估算

获取原文

摘要

This paper proposes a new privacy-preserving scheme for estimating the size of the intersection of two given secret subsets. Given the inner product of two Bloom filters (BFs) of the given sets, the proposed scheme applies Bayesian estimation under assumption of beta distribution for an a priori probability of the size to be estimated. The BF retains the communication complexity and the Bayesian estimation improves the estimation accuracy. An possible application of the proposed protocol is an epidemiological datasets regarding two attributes, Helicobactor pylori infection and stomach cancer. Assuming information related to Helicobactor Pylori infection and stomach cancer are separately collected, the protocol demonstrates that a χ~2-test can be performed without disclosing the contents of the two confidential databases.
机译:本文提出了一种新的隐私保留方案,用于估算两个给定秘密子集的交叉点的大小。鉴于给定集合的两个绽放过滤器(BFS)的内部产物,所提出的方案在假设估计尺寸的概要概率的情况下,达到贝叶斯估计。 BF保留通信复杂性,贝叶斯估计提高了估计准确性。所提出的协议的可能应用是有关两个属性的流行病学数据集,直升机幽门螺杆菌感染和胃癌。假设分别收集与Helicobactor Pylori感染和胃癌有关的信息,方案表明,可以进行χ〜2测试,而无需公开两个机密数据库的内容。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号