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隐私集合运算中的关键数据结构研究OA北大核心CSTPCD

A Survey on Key Data Structures in Private Set Operation

中文摘要英文摘要

隐私集合运算(private set operation,PSO)是安全多方计算领域的热点问题,它允许两个参与方对各自私有集合进行安全计算,同时避免额外信息泄露.常见的PSO协议包括隐私集合求交和隐私集合求并.高效的隐私集合运算协议的设计与多种高级的数据结构密切相关.然而,目前隐私集合运算中各种数据结构缺乏系统梳理且无同一平台上的效率对比结果.本文将PSO中的关键数据结构分为三类,分别是哈希表、过滤器和不经意键值存储.在明确各类数据结构的基本定义与构造方式的基础上,本文梳理各数据结构的主要功能作用、总结它们在不同协议中的典型应用、探讨它们在PSO中的研究现状与主要进展,并提供各数据结构的性能对比分析与基准测试结果.

Private set operation(PSO)is a hot topic in the field of secure multi-party computation.It allows two parties to perform secure computations on their own private sets without information leakage.Generally,PSO protocols include private set intersection(PSI)and private set union(PSU)operations.Advanced data structures play an important role in the design of efficient PSO protocols.However,there is a lack of systematic overview of various data structures in PSO and no uniform efficiency comparison on the same platform among them is provided.This paper classifies the key data structures deployed in existing PSO protocols into three categories:hashing tables,filters,and oblivious key-value stores.After clarifying the basic definitions and constructions of each data structure,this paper compares their main features,summarizes their typical applications,discusses their current research status and main progress in PSO,and provides performance analysis and benchmark results for each data structure.

张响鸰;张聪;刘巍然;陈宇

山东大学网络空间安全学院,青岛 266237||泉城实验室,济南 250103||密码科学技术全国重点实验室,北京 100878清华大学高等研究院,北京 100084阿里巴巴集团,北京 100120泉城实验室,济南 250103||山东大学网络空间安全学院,青岛 266237||密码科学技术全国重点实验室,北京 100878

计算机与自动化

隐私集合运算数据结构安全多方计算

private set operationdata structuresecure multi-party computation

《密码学报》 2024 (002)

263-281 / 19

国家重点研发计划(2021YFA1000600);国家自然科学基金(62272269);泰山学者青年专家;山东省科技厅山东省实验室项目(SYS202201);泉城实验室重点项目(QCLZD202302);国家社科基金重大项目(22&ZD147)National Key Research and Development Program of China(2021YFA1000600);National Natural Science Foundation of China(62272269);Taishan Scholar Program of Shandong Province;Shandong Laboratories Project of Bureau of Science & Technology of Shandong Province(SYS202201);Key Project of Quan Cheng Laboratory(QCLZD202302);Major Programs of National Social Science Foundation of China(22&ZD147)

10.13868/j.cnki.jcr.000679

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