Information-Theoretic Multi-Server PIR with Global Preprocessing

We propose a new unified framework to construct multi-server, information-theoretic Private Information Retrieval (PIR) schemes that leverage global preprocesing to achieve sublinear computation per query. Despite a couple earlier attempts, our understanding of PIR schemes in the global preprocessing model remains limited, and so far, we only know a few sparse points in the broad design space. With our new unified framework, we can generalize the results of Beimel, Ishai, and Malkin to broader parameter regimes, thus enabling a tradeoff between bandwidth and computation. Specifically, for any constant S > 1 , we can get an S -server scheme whose bandwidth consumption is as small as n 1 / ( S +1)+ (cid:15) while achieving computation in the n δ regime for some constant δ ∈ (0 , 1) . Moreover, we can get a scheme with polylogarithmic bandwidth and computation, requiring only polylogarithmic number of servers.

我们提出了一个新的统一框架，以构建多服务器，信息理论的私人信息检索（PIR）方案，该方案利用全局预处理以实现每个查询的均等计算，尽管我们对全球预审查模型中的PIR方案的理解仍然存在。到目前为止，我们只知道广泛的设计空间中的一些稀疏点。 Ishai和Malkin到更广泛的参数制度，因此可以在带宽和计算之间进行权衡。 +（CID：15）在某些常数δ∈（0，1）中实现Nδ制度的计算时，我们可以获得具有polygarithmic bandmic带宽和计算的方案，仅需要多个服务器数量。