Classical Mechanism is Optimal in Classical-Quantum Differentially Private Mechanisms

Yuuya Yoshida, Masahito Hayashi
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引用次数: 5

Abstract

Differential privacy (DP) is an influential privacy measure and has been studied to protect private data. DP has been often studied in classical probability theory, but few researchers studied quantum versions of DP. In this paper, we consider classical-quantum DP mechanisms which (i) convert binary private data to quantum states and (ii) satisfy a quantum version of the DP constraint. The class of classical-quantum DP mechanisms contains classical DP mechanisms. As a main result, we show that some classical DP mechanism optimizes any information quantity satisfying the information processing inequality. Therefore, the performance of classical DP mechanisms attains that of classical-quantum DP mechanisms.
经典机制在经典量子微分私有机制中是最优的
差分隐私(DP)是一种很有影响力的隐私措施,被研究用于保护隐私数据。在经典概率论中对概率预测进行了较多的研究,但对量子概率预测的研究却很少。在本文中,我们考虑经典量子DP机制,它(i)将二进制私有数据转换为量子态,(ii)满足DP约束的量子版本。经典量子DP机制包含经典DP机制。主要结果表明,某些经典的DP机制对满足信息处理不等式的任意信息量都是最优的。因此,经典DP机制的性能达到了经典量子DP机制的性能。
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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