信息安全研究2024，Vol.10Issue(1)：6-11,6.DOI:10.12379/j.issn.2096-1057.2024.01.02
安全多方计算应用的隐私度量方法
Privacy Measures for Secure Multi-party Computing Applications
熊维 1王海洋 2唐祎飞 3刘伟1
作者信息
- 1. 神州融安数字科技(北京)有限公司 北京 100086
- 2. 北京国际大数据交易有限公司 北京 100020
- 3. 大数据协同安全技术国家工程研究中心 北京 100071
- 折叠
摘要
Abstract
The privacy protection ability of secure multi-party computing application to input information depends on the underlying security mechanism on the one hand,and on the other hand depends on the task functions.At present,the research on secure multi-party computing mainly focuses on the security mechanism to prevent information leakage in the process of computing.However,there are few studies on the measure of task functions'ability to protect the input information of the participants.The problem that each participant of the task function deduces the input information of other participants through the legitimate input and output cannot be prevented by the security mechanism of secure multi-party computing,so the measurements of the privacy protection power of the task function are related to the concrete implementation and application of secure multi-party computing schemes.In this paper,according to the information entropy model,the concepts of average entropy and specific entropy are defined from the point of view of the attacker,and a method to calculate information benefits is proposed.Then,the privacy protection strength of the specific application scheme of secure multi-party computing schemes is measured by calculating the ideal privacy loss of the objective function and the actual privacy loss of the actual secure multi-party computing application.关键词
安全多方计算/隐私度量/信息熵/计算信息收益/隐私损耗Key words
secure multi-party computing/privacy metric/information entropy/computing information benefits/privacy loss分类
信息技术与安全科学引用本文复制引用
熊维,王海洋,唐祎飞,刘伟..安全多方计算应用的隐私度量方法[J].信息安全研究,2024,10(1):6-11,6.
