Privacy for multi-party protocols

Wanqing Wu, LingNa Guo, Ming-Zhe Xie

The goal of semi-quantum privacy comparison (SQPC) is to use a small amount of quantum capabilities to compare private information for equality. In recent years, research on semi-quantum privacy comparison protocol has made some achievements. However, most of SQPC protocols can merely compare the private information of two parties, and the research of multi-party SQPC protocols are still scarce. If the number of participants is more than two, the protocol needs to be executed multiple times. Therefore, we proposed a multi-party semi-quantum private comparison protocol based on the maximally entangled GHZ-type state, which has the capability to compare the equality of n parties by executing the protocol once. What is more, the transmission of participant’s encrypted information is not through the classical channel, which improves the security of the protocol. Finally, the security analysis shows that outsider attacks, dishonest participants attacks and semi-honest TP attacks are all invalid for this protocol.

Donald Beaver

Zhichao Zhao

Ye Wang, Prakash Ishwar

In the problem of secure multi-party sampling, n parties wish to securely sample an n-variate joint distribution, with each party receiving a sample of one of the correlated variables. The objective is to correctly produce the samples using a distributed message passing protocol, while maintaining privacy against a coalition of passively cheating parties. In the two-party case, we fully characterize the joint distributions that can be securely sampled under perfect correctness and privacy requirements as well as under weakened correctness and privacy requirements. Furthermore, we show that the distributions that can be securely sampled can be produced with a protocol that only uses one round of unidirectional communication. For the n-party case, any distribution can be securely sampled with privacy against a strict minority coalition, due to well-known results in secure multi-party computation. However, when privacy against a majority coalition is required, not all distributions can be securely sampled. We give necessary conditions and sufficient conditions for distributions that can be securely sampled. However, the exact characterization of the distributions that can be securely sampled remains open.

Keith B. Frikken, Mikhail J. Atallah

Yi Zhou, Yao‐Fei Wu, Xiang-Rui Li +2 more

ABSTRACT As an important branch of quantum‐secure multi‐party computation, quantum‐secure multi‐party computational geometry aims to solve geometric computation problems without revealing the parties' geometric inputs. Privacy‐preserving point‐circle and circle‐circle positional relationships are classic problems in secure multi‐party computational geometry, with broad applications in privacy‐preserving queries, collision detection, and clustering. Building on the quantum two‐party summation and multiplication protocols proposed by Sutradhar and Om, this paper presents the first quantum‐secure protocols for determining point‐circle and circle‐circle positional relationships, enabling accurate relationship determination without disclosing private geometric parameters. Security analysis and simulation experiments on the IBM Qiskit platform demonstrate the security and feasibility of the proposed protocols. Furthermore, since existing quantum privacy‐preserving range query protocols are limited to one‐dimensional linear spaces, we build on the proposed protocols to present the first quantum‐secure privacy‐preserving geometric range query protocol, which enables arbitrary geometric range search for private coordinates in the two‐dimensional space while protecting the privacy of the query range and data points.