Work

Mathematical comparison of classical and quantum mechanisms in optimization under local differential privacy

Year: 2024

Type: article

Abstract: Differential privacy (DP) is an influential method of protecting private data, and is a condition for a conditional probability distribution. Since we can regard DP as a condition for a tuple of probability vectors, it is natural to consider a similar condition for a tuple of density matrices as a quantum version of DP. This condition is called classical-quantum DP (CQ-DP) because it is considered in converting classical data to quantum states. In the study of DP (including CQ-DP), a positive parameter ɛ represents the privacy level to be guaranteed. In this paper, we show that CQ-DP has a quantum advantage in certain optimization problems. Moreover, we compare classical DP and CQ-DP mathematically to clarify a relation between privacy level and quantum advantage.

Source: Journal of Physics A Mathematical and Theoretical

DOI: 10.1088/1751-8121/ada0f9

Author: Yuuya Yoshida

Institution: Nagoya Institute of Technology

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,165

Funder: Japan Society for the Promotion of Science