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基于量子密码学的可证明安全的对称私有信息检索

Provably Secure Symmetric Private Information Retrieval with Quantum Cryptography.

作者信息

Kon Wen Yu, Lim Charles Ci Wen

机构信息

Department of Electrical & Computer Engineering, National University of Singapore, Singapore 119077, Singapore.

Centre for Quantum Technologies, National University of Singapore, Singapore 119077, Singapore.

出版信息

Entropy (Basel). 2020 Dec 31;23(1):54. doi: 10.3390/e23010054.

Abstract

Private information retrieval (PIR) is a database query protocol that provides user privacy in that the user can learn a particular entry of the database of his interest but his query would be hidden from the data centre. Symmetric private information retrieval (SPIR) takes PIR further by additionally offering database privacy, where the user cannot learn any additional entries of the database. Unconditionally secure SPIR solutions with multiple databases are known classically, but are unrealistic because they require long shared secret keys between the parties for secure communication and shared randomness in the protocol. Here, we propose using quantum key distribution (QKD) instead for a practical implementation, which can realise both the secure communication and shared randomness requirements. We prove that QKD maintains the security of the SPIR protocol and that it is also secure against any external eavesdropper. We also show how such a classical-quantum system could be implemented practically, using the example of a two-database SPIR protocol with keys generated by measurement device-independent QKD. Through key rate calculations, we show that such an implementation is feasible at the metropolitan level with current QKD technology.

摘要

私密信息检索(PIR)是一种数据库查询协议,它能提供用户隐私保护,即用户可以获取其感兴趣的数据库中的特定条目,但数据中心无法知晓其查询内容。对称私密信息检索(SPIR)在PIR的基础上进一步提供了数据库隐私保护,即用户无法获取数据库中的任何其他条目。经典的无条件安全的多数据库SPIR解决方案是已知的,但不切实际,因为它们需要各方之间有长的共享密钥用于安全通信以及协议中的共享随机性。在此,我们提出使用量子密钥分发(QKD)来实现实际应用,它可以满足安全通信和共享随机性的要求。我们证明了QKD能维持SPIR协议的安全性,并且对任何外部窃听者也是安全的。我们还展示了如何以一个由测量设备无关QKD生成密钥的双数据库SPIR协议为例,实际实现这样一个经典 - 量子系统。通过密钥率计算,我们表明利用当前的QKD技术,这种实现在城域级别是可行的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a14f/7823359/b0dabdcce2f6/entropy-23-00054-g001.jpg

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