Abstract Secure multiparty computational geometry is an essential field of secure multiparty computation. It involves solving geometric problems without disclosing any private geometric information from each participating party. Privacy-preserving point-line relation determination, a pivotal branch of secure multiparty computational geometry, holds significant potential for applications in various domains, including business, engineering, and military. In this paper, leveraging the assistance of a third party, we introduce a quantum solution to privacy-preserving point-line relation determination. This approach incorporates quantum key distribution and one-time pad encryption. Under the condition that the third party does not conspire with any participant, our protocol ensures heightened security and enhanced privacy protection compared to classical methods. This superiority is attributed to the underlying principles of quantum mechanics and the utilization of one-time pad encryption. Furthermore, we extend our protocol to involve multiple third parties, employing the technology of quantum secret sharing. In scenarios where these third parties refrain from colluding with any single participant, no information is divulged to the other participant. Consequently, the protocol becomes more rational and secure when multiple third parties are involved.
Abstract Secure Multiparty Computation (MPC) is a cryptography technique that allows multiple parties to securely perform operations on their private inputs without revealing them. It is used in various applications, such as data aggregation in the cloud, IoT, etc., where data privacy is the prime concern. Many researchers have explored ways to develop secure protocols with minimal risk of data leakage. Many of these classical secure MPC protocols depend on classical random number generators. However, advances in quantum information processing are putting classical key distribution methods at risk. Traditional summation protocols adopt an
((n,n)) threshold approach, requiring the participation of all
(n) players to compute the sum securely. However, the proposed quantum secure multiparty computation based on secure summation and QKD (QSMPC-SSQKD) introduces a generalised quantum secure multiparty summation protocol. The proposed protocol utilises entanglement, a fundamental property of quantum mechanics, to facilitate safe key exchange, thereby ensuring robust security measures. We use a quantum random number generator (QRNG) to generate true random numbers, ensuring privacy preservation. The protocol achieves a per-bit entropy level of 0.708 through QRNG, which provides strong randomness. The security of the proposed protocol is validated using the CHSCH test (
(B≈2.8)), ensuring that any attempt to eavesdrop on the system can be detected, and the complete process will be rescheduled. Compared to some similar protocols, the proposed QSMPC-SSQKD protocol provides higher randomness and lower quantum circuit cost without using any trusted third party (TTP). This improvement enhances the protocol’s efficiency and practicality in preventing data leakage during computation.
Secure two-party scalar product (S2SP) is a promising research area within secure multiparty computation (SMC), which can solve a range of SMC problems, such as intrusion detection, data analysis, and geometric computations. However, existing quantum S2SP protocols are not efficient enough, and the complexity is usually close to exponential level. In this paper, a novel secure two-party quantum scalar product (S2QSP) protocol based on Fourier entangled states is proposed to achieve higher efficiency. Firstly, the definition of unconditional security under malicious models is given. And then, an honesty verification method called Entanglement Bondage is proposed, which is used in conjunction with the modular summation gate to resist malicious attacks. The property of Fourierentangled states is used to calculate the scalar product with polynomial complexity. The unconditional security of our protocol is proved, which guarantees the privacy of all parties. In addition, we design a privacy-preserving quantum matrix multiplication protocol based on S2QSP protocol. By transforming matrix multiplication into a series of scalar product processes, the product of two private matrices is calculated without revealing any privacy. Finally, we show our protocol’s feasibility in IBM Qiskit simulator.