Year: 2025
Type: article
Abstract: Quantum Anonymous Multi-party Ranking (QAMR) enables quantum ranking operations to be performed on private datasets while concealing associations between participants and their private data. However, most existing protocols rely on semi-honest third parties and require the use of a large number of quantum states to ensure identity anonymity. Furthermore, they lack transferability due to inadequate modular design. To address these issues, a novel QAMR protocol is proposed, which eliminates the need for semi-honest third parties for the first time. The protocol achieves reduced quantum resource consumption while ensuring transferability. Moreover, the protocol’s correctness is proven by theoretical analysis, and its feasibility is confirmed via IBM Qiskit simulations. A thorough security analysis shows that the protocol is resistant to collusion, entanglement-measurement, and intercept-resend attacks. Besides, the comparison shows that the suggested approach uses fewer quantum resources while processing datasets with wider distributions and higher limits.
Source: EPJ Quantum Technology
Authors: Xinyue Mao, Huixin Sun, Jiuru Wang, Kejia Zhang, Baomin Zhou
Institutions: Heilongjiang University, Linyi University, Guizhou University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,190
OpenAlex ID: W4414595292