Ishai et al. (FOCS'06) introduced secure shuffling as an efficient building block for private data aggregation. Recently, the field of differential privacy has revived interest in secure shufflers by highlighting the privacy amplification they can provide in various computations. Although several works argue for the utility of secure shufflers, they often treat them as black boxes; overlooking the practical vulnerabilities and performance trade-offs of existing implementations. This leaves a central question open: what makes a good secure shuffler? This survey addresses that question by identifying, categorizing, and comparing 26 secure protocols that realize the necessary shuffling functionality. To enable a meaningful comparison, we adapt and unify existing security definitions into a consistent set of properties. We also present an overview of privacy-preserving technologies that rely on secure shufflers, offer practical guidelines for selecting appropriate protocols, and outline promising directions for future work.
翻译:Ishai等人(FOCS'06)将安全洗牌引入作为私有数据聚合的高效构建模块。近年来,差分隐私领域通过强调安全洗牌器在各种计算中可提供的隐私增强效应,重新激发了对其的研究兴趣。尽管多项研究论证了安全洗牌器的实用性,但常将其视为黑盒;忽视了现有实现中的实际漏洞与性能权衡。这导致一个核心问题悬而未决:何为良好的安全洗牌器?本综述通过识别、分类并比较26种实现必要洗牌功能的安全协议来回答该问题。为实现有意义的比较,我们调整并统一了现有安全定义,形成一组一致的性质描述。同时,我们概述了依赖安全洗牌器的隐私保护技术,提供了选择适用协议的实用指南,并指出了未来工作的潜在方向。