Private Information Retrieval in Large Scale Public Data Repositories

IF 2.6 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Proceedings of the Vldb Endowment Pub Date : 2023-08-01 DOI:10.14778/3611540.3611572

Ishtiyaque Ahmad, Divyakant Agrawal, Amr El Abbadi, Trinabh Gupta

引用次数: 0

Abstract

The tutorial focuses on Private Information Retrieval (PIR), which allows clients to privately query public or server-owned databases without disclosing their queries. The tutorial covers the basic concepts of PIR such as its types, construction, and critical building blocks, including homomorphic encryption. It also discusses the performance of PIR, existing optimizations for scalability, real-life applications of PIR, and ways to extend its functionalities.

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大规模公共数据库中的私有信息检索

本教程重点介绍私有信息检索(Private Information Retrieval, PIR)，它允许客户机在不公开其查询的情况下私下查询公共或服务器拥有的数据库。本教程介绍了PIR的基本概念，例如它的类型、构造和关键构建块，包括同态加密。本文还讨论了PIR的性能、现有的可伸缩性优化、PIR的实际应用程序以及扩展其功能的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Proceedings of the Vldb Endowment Computer Science-General Computer Science

CiteScore

7.70

自引率

0.00%

发文量

期刊介绍： The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.