全分布式鲁棒安全多方计算的匿名系统

Andreas Klinger, Felix Battermann, Ulrike Meyer
{"title":"全分布式鲁棒安全多方计算的匿名系统","authors":"Andreas Klinger, Felix Battermann, Ulrike Meyer","doi":"10.1145/3577923.3583651","DOIUrl":null,"url":null,"abstract":"In secure multi-party computation (SMPC), it is considered that multiple parties that are known to each other evaluate a function over their private inputs in a secure fashion. The participating parties do not learn anything about each other's private inputs beyond what can be deduced from their own input and output. The assumption that the parties know each other, however, does not seem suitable for all potential applications of SMPC. In some applications participants may not only want to hide their private inputs and outputs, but may also want to hide the fact that they are participating in a given function evaluation in the first place. We therefore propose an anonymous system for SMPC that allows parties to anonymously evaluate a function of their private inputs in a fully distributed and secure fashion. The proposed system allows authorized parties to execute an SMPC protocol robust with penalty against a dishonest majority in the presence of a malicious adversary. During the protocol execution, the system guarantees that all participating parties stay anonymous w. r. t. each other as well as any third parties. In addition, it guarantees that in each function evaluation all participating parties are unique, i. e., no party can participate as more than one entity.","PeriodicalId":387479,"journal":{"name":"Proceedings of the Thirteenth ACM Conference on Data and Application Security and Privacy","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Anonymous System for Fully Distributed and Robust Secure Multi-Party Computation\",\"authors\":\"Andreas Klinger, Felix Battermann, Ulrike Meyer\",\"doi\":\"10.1145/3577923.3583651\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In secure multi-party computation (SMPC), it is considered that multiple parties that are known to each other evaluate a function over their private inputs in a secure fashion. The participating parties do not learn anything about each other's private inputs beyond what can be deduced from their own input and output. The assumption that the parties know each other, however, does not seem suitable for all potential applications of SMPC. In some applications participants may not only want to hide their private inputs and outputs, but may also want to hide the fact that they are participating in a given function evaluation in the first place. We therefore propose an anonymous system for SMPC that allows parties to anonymously evaluate a function of their private inputs in a fully distributed and secure fashion. The proposed system allows authorized parties to execute an SMPC protocol robust with penalty against a dishonest majority in the presence of a malicious adversary. During the protocol execution, the system guarantees that all participating parties stay anonymous w. r. t. each other as well as any third parties. In addition, it guarantees that in each function evaluation all participating parties are unique, i. e., no party can participate as more than one entity.\",\"PeriodicalId\":387479,\"journal\":{\"name\":\"Proceedings of the Thirteenth ACM Conference on Data and Application Security and Privacy\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Thirteenth ACM Conference on Data and Application Security and Privacy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3577923.3583651\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Thirteenth ACM Conference on Data and Application Security and Privacy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3577923.3583651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在安全多方计算(SMPC)中,认为彼此已知的多方以安全的方式对其私有输入的函数进行评估。除了可以从自己的投入和产出中推断出来的东西外,参与各方对彼此的私人投入一无所知。然而,假设双方彼此认识,似乎并不适用于SMPC的所有潜在应用。在一些应用程序中,参与者可能不仅希望隐藏他们的私有输入和输出,而且还希望首先隐藏他们正在参与给定函数求值的事实。因此,我们为SMPC提出了一个匿名系统,允许各方以完全分布式和安全的方式匿名评估其私人输入的函数。提出的系统允许授权方执行SMPC协议,在恶意对手存在的情况下,对不诚实的大多数进行惩罚。在协议执行过程中,系统保证所有参与方之间以及任何第三方都保持匿名。此外,它保证了在每个函数评估中,所有参与方都是唯一的,即任何一方都不能作为一个以上的实体参与。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anonymous System for Fully Distributed and Robust Secure Multi-Party Computation
In secure multi-party computation (SMPC), it is considered that multiple parties that are known to each other evaluate a function over their private inputs in a secure fashion. The participating parties do not learn anything about each other's private inputs beyond what can be deduced from their own input and output. The assumption that the parties know each other, however, does not seem suitable for all potential applications of SMPC. In some applications participants may not only want to hide their private inputs and outputs, but may also want to hide the fact that they are participating in a given function evaluation in the first place. We therefore propose an anonymous system for SMPC that allows parties to anonymously evaluate a function of their private inputs in a fully distributed and secure fashion. The proposed system allows authorized parties to execute an SMPC protocol robust with penalty against a dishonest majority in the presence of a malicious adversary. During the protocol execution, the system guarantees that all participating parties stay anonymous w. r. t. each other as well as any third parties. In addition, it guarantees that in each function evaluation all participating parties are unique, i. e., no party can participate as more than one entity.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信