Multiparty Quantum Private Comparison Protocol Using n -Particle GHZ State

Min Hou, Yue Wu and Shibin Zhang ()
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Min Hou: School of Computer Science, Sichuan University Jinjiang College, Meishan 620860, China
Yue Wu: School of Computer Science, Sichuan University Jinjiang College, Meishan 620860, China
Shibin Zhang: College of Artificial Intelligence, Chengdu University of Information Technology, Chengdu 610225, China

Mathematics, 2025, vol. 13, issue 21, 1-14

Abstract: Multiparty quantum private comparison (MQPC) aims to determine the equality relationship of inputs from multiple participants while maintaining the confidentiality of these inputs. Current MQPC protocols primarily focus on utilizing d -level quantum states, which limits feasible implementation. To address this issue, we introduce an MQPC protocol that utilizes n -particle Greenberger–Horne–Zeilinger (GHZ) state to enable private comparison while preserving the secrecy of individual inputs. A semi-honest third party (TP), adhering to protocol specifications but potentially curious about private data, generates and distributes GHZ state qubits to all participants. Each party encodes their secret input through rotation operations on their allocated qubits and returns the modified state to the TP, which then performs single-particle quantum measurements to derive the outcomes without accessing the raw inputs. The protocol’s sequence distribution method yields a high qubit efficiency of 1/ n , outperforming many existing MQPC protocols. Security analysis confirms resilience against external adversaries employing quantum attack strategies and collusion attempts among participants. Simulations using IBM Qiskit validate the feasibility of the protocol, which relies on GHZ state preparation, single-qubit operations, and single-particle quantum measurements.

Keywords: multiparty quantum private comparison; n -particle GHZ state; rotation operation; quantum secure multiparty computation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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