双盲比较：解决数据库聚集问题的一种新方法
Double Blind Comparisons: A New Approach to the Database Aggregation Problem
摘要：
当大量数据集合的安全级别高于其任何单个组件记录时，就会发生数据聚合问题。传统的方法是将数据分解，并在“需要知道”的基础上限制访问，这首先剥夺了收集数据的巨大优势之一。本文介绍了一种新的密码原语，双盲比较，它允许两个合作的用户，谁都有一个加密的秘密，以确定这两个秘密的平等或不平等，即使没有用户可以发现任何信息的秘密是什么。本文还介绍了双线性群中的一个新问题，它被证明是一个困难问题。假设这个猜想，它表明，没有用户的合作，任何用户都不能发现任何信息的秘密是否是平等的。然后，我们将研究如何使用双盲比较来缓解数据聚合问题。最后，本文的结论与未来的研究和一些其他潜在的双盲比较的可能性。
英文摘要：
The Data Aggregation Problem occurs when a large collection of data takes on a higher security level than any of its individual component records. Traditional approaches of breaking up the data and restricting access on a "need to know" basis take away one of the great advantages of collecting the data in the first place. This paper introduces a new cryptographic primitive, Double Blind Comparisons, which allows two co-operating users, who each have an encrypted secret, to determine the equality or inequality of those two secrets, even though neither user can discover any information about what the secret is. This paper also introduces a new problem in bilinear groups, conjectured to be a hard problem. Assuming this conjecture, it is shown that neither user can discover any information about whether the secrets are equal, without the other user's co-operation. We then look at how Double Blind Comparisons can be used to mitigate the Data Aggregation Problem. Finally, the paper concludes with some suggested possibilities for future research and some other potential uses for Double Blind Comparisons.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
