A novel quantum anonymous ranking protocol

Justin Joseph, Syed Taqi Ali

Qingle Wang, Yuancheng Li, Chaohang Yu +2 more

Wei Huang, Qiaoyan Wen, Bin Liu +3 more

Anonymous ranking is a kind of privacy-preserving ranking whereby each of the involved participants can correctly and anonymously get the rankings of his data. It can be utilized to solve many practical problems, such as anonymously ranking the students' exam scores. We investigate the issue of how quantum mechanics can be of use in maintaining the anonymity of the participants in multiparty ranking and present a series of quantum anonymous multiparty, multidata ranking protocols. In each of these protocols, a participant can get the correct rankings of his data and nobody else can match the identity to his data. Furthermore, the security of these protocols with respect to different kinds of attacks is proved.

Xinyue Mao, Huixin Sun, Jiuru Wang +2 more

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.

Yuan Li, Guihua Zeng

Justin Joseph, Syed Taqi Ali

Abstract We propose a quantum secure multiparty multidata ranking (QSMMR) protocol based on quantum walks. Our protocol improves the traditional anonymous ranking protocol to secure ranking, where we ensure the confidentiality of the data. A quantum anonymous ranking protocol exposes all participants’ data, which is not ideal for practical scenarios such as personal wealth and health indexes. Hence, we propose the first quantum secure ranking protocol with semi-honest TP, that generates ranking for multiple data of multiple participants by keeping data completely secure. We use quantum resources to assign a random address to all participants, to perform comparison, and for the eavesdropper detection. Finally, we analyze and prove the security of the protocol.