One way to classify private set intersection (PSI) for secure 2-party computation is whether the intersection is (a) revealed to both parties or (b) hidden from both parties while only the computing function of the matched payload is exposed. Both aim to provide cryptographic security while avoiding exposing the unmatched elements of the other. They may, however, be insufficient to achieve security and privacy in one practical scenario: when the intersection is required and the information leaked through the function's output must be considered for legal, ethical, and competitive reasons. Two parties, such as the advertiser and the ads supplier, hold sets of users for PSI computation, for example, to reveal common users to the ads supplier in joint marketing applications. In addition to the security guarantees required by standard PSIs to secure unmatched elements, neither party is allowed to "single out" whether an element/user belongs to the other party or not, even though common users are required for joint advertising. This is a fascinating problem for which none of the PSI techniques have provided a solution. In light of this shortcoming, we compose differential privacy (DP) and S2PC to provide the best of both worlds and propose differentially-private PSI (DP-PSI), a new privacy model that shares PSI's strong security protection while adhering to the GDPR's recent formalization of the notion of excluding "signaling out" attacks by each party except with very low probability.
翻译:用于安全两方计算私基交叉路口(PSI)的分类方法之一是,交叉路口是(a)向双方披露,还是(b)向双方隐瞒,而只有匹配的有效载荷的计算功能才暴露,两者的目的都是提供加密安全,同时避免暴露不匹配的其他要素;然而,在一种实际情况下,它们可能不足以实现安全和隐私:当需要交叉路口时,而且由于法律、道德和竞争原因必须考虑该函数输出中泄漏的信息时,这是一个令人着迷的问题,例如广告商和广告供应商等两方都持有一套PSI计算用户,例如,在联合营销应用程序中向供应商披露共同用户。除了标准PSI要求的加密安全保证外,标准PSI要求的加密安全保障措施之外,任何一方都不得“退出”某一要素/用户属于另一方,即使需要共同用户来做联合广告。这是一个很有意思的问题,而低的PSI技术没有提供解决办法。鉴于这一缺陷,我们将隐私差异性(DP)和SSI的保密性价比(SIPI)概念都提供了最佳的安全保护。