小,笨,可扩展:安全计算与游戏

A. Iliev, Sean W. Smith
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引用次数: 19

摘要

阿格尼斯怎么能相信鲍里斯电脑上的计算呢?特别是,在Boris甚至无法观察到C的内部状态的情况下,Agnes怎么能相信C正在发生?一种方法是让艾格尼丝把C存储在鲍里斯的地方一个强大的防篡改安全协处理器中。然而,这种方法是不可扩展的:无论是在计算方面——一旦C变得比协处理器大,它就会再次受到Boris的攻击——还是在成本方面。在本文中,我们报告了我们的Faerieplay项目:与其担心安全协处理器的有限尺寸,不如尝试让它尽可能小,使用有限的RAM和CPU。我们从Malkhi等人的Fairplay工作开始,该工作实现了Yao的盲电路解决方案,通过软件保护多方计算——这允许Agnes信任C,但对于除了小C之外的所有C来说都太低效了。然后,我们使用自己之前的工作,使用可信第三方进行实际的私人信息检索,设计和原型微型可信第三方(tthttps),这大大减少了盲电路评估所涉及的开销。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Small, stupid, and scalable: secure computing with faerieplay
How can Agnes trust a computation C occurring at Boris's computer? In particular, how can Agnes can trust that C is occurring without Boris even being able to observe its internal state? One way is for Agnes to house C in a strong tamper-protected secure coprocessor at Boris's site. However, this approach is not scalable: neither in terms of computation - once C gets larger than the coprocessor, it becomes vulnerable to Boris again - nor in terms of cost. In this paper, we report on our Faerieplay project: rather than worrying about the limited size of a secure coprocessor, we try to make it as small as possible, with limited RAM and CPU. We start with the Fairplay work of Malkhi et al on implementing Yao's blinded-circuit solution to secure multiparty computation with software - this permits Agnes to trust C, but is too inefficient for all but small C. We then use our own prior work on using trusted third parties for practical Private Information Retrieval to design and prototype tiny trusted third parties (TTTPs) that substantially reduce the overhead involved in blind circuit evaluation.
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