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Bristol/Bar-Ilan MPC

布里斯托尔/巴伊兰 MPC

基本信息

批准号：
EP/M012824/1
负责人：
Nigel Smart
金额：
$ 25.57万
依托单位：
University of Bristol
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2015
资助国家：
英国
起止时间：
2015 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FM012824%2F1
关键词：
Bristol Bar Ilan MPC

项目摘要

Secure two-party and multiparty computation enables a set of parties with private inputs to securely compute a joint function of their inputs. The security properties guaranteed are privacy (nothing but the output is revealed), correctness (the correct output is obtained, even if some parties behave maliciously), and independence of inputs (no party can make its input depend on other parties' inputs). In the case where a majority of the participating parties can be assumed to be honest, then it is also possible to guarantee fairness (meaning that if one party obtains output then all parties obtain output). These security properties must hold in the face of adversarial behaviour. Despite the stringent requirements on protocols for secure computation, it was already shown in the mid 1980s that any efficient function can be securely computed in the presence of malicious adversaries. This powerful feasibility result has enormous implications! Any distributed task between machines which may or may not be honest (either because the party owning the machine is dishonest, or the machine has been hacked into and taken over by an adversary) can be carried out securely, without any concern that private information will be stolen, or that an incorrect result may be obtained. Thus, secure computation can be used to solve a vast number of problems that occur in the modern digital era. These problems include auctions, elections, digital cash, anonymous transactions, private database queries, cloud security, privacy-preserving data mining, private statistics aggregation, private biometric verification, and more. This potential and broad applicability has made secure computation a heavily-studied field over the last 25 years.The proposal will solidify the existing research collaboration between the University of Bristol and Bar-Ilan University, and will aim to integrate the two distinct approaches to practical MPC which have been developed in the two institutions over the last few years.

安全的两方和多方计算使一组具有私有输入的各方能够安全地计算其输入的联合函数。保证的安全属性是隐私（只显示输出），正确性（即使某些方的行为是恶意的，也会获得正确的输出）和输入的独立性（任何一方都不能使其输入依赖于其他方的输入）。在大多数参与方可以被假设为诚实的情况下，也可以保证公平性（这意味着如果一方获得输出，则所有各方都获得输出）。这些安全属性必须在对抗行为面前保持不变。尽管对安全计算的协议有严格的要求，但在20世纪80年代中期已经表明，任何有效的函数都可以在恶意对手存在的情况下安全地计算。这个强大的可行性结果具有巨大的意义！机器之间的任何分布式任务都可以安全地执行，而不必担心私人信息会被窃取，或者可能会获得错误的结果。因此，安全计算可用于解决现代数字时代出现的大量问题。这些问题包括拍卖、选举、数字现金、匿名交易、私有数据库查询、云安全、隐私保护数据挖掘、私有统计数据聚合、私有生物特征验证等。这种潜在的和广泛的适用性使得安全计算在过去25年里成为一个被广泛研究的领域。该提案将巩固布里斯托大学和巴伊兰大学之间现有的研究合作，并将旨在整合两个不同的方法，以实现在过去几年中在两个机构中开发的实用MPC。