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Secure multiparty computation based on quantum technologies

Zeinab Rahmani

Published Jul 15, 2025• 0 citations
OpenAlex

Abstract

Secure Multiparty Computation (SMC) allows multiple individuals, each having their own private data, to perform a computation task without unveiling their data to others. SMC has a wide range of real-life use cases, including machine learning, vehicular networks, banking, defense, and healthcare. However, classical SMC implementations face significant challenges related to both security and efficiency. Classical SMC protocols rely on public-key cryptographic methods, which introduce substantial computational and communication costs. Additionally, these protocols are vulnerable to quantum computer attacks that have the potential to break certain types of cryptographic ciphers, notably those used in RSA. In this thesis, we tackle these challenges by enhancing the security and efficiency of SMC implementations through quantum communication and quantum computing. Quantum communication contributes to enhancing security, while quantum computing, by leveraging quantum processors, offers the potential to significantly improve efficiency. In the quantum communication approach, we propose a Quantum SMC (QSMC) framework that leverages three advanced quantum communication technologies - Quantum Random Number Generation (QRNG), Quantum Key Distribution (QKD), and Quantum Oblivious Key Distribution (QOKD)—in conjunction with a Key Management System (KMS) and the Faster Malicious Arithmetic Secure Computation with Oblivious Transfer (MASCOT) protocol. Exploiting the proposed framework, we implement two essential SMC use cases: Safe Route Departure (SRD) and Drug Solubility Prediction (DSP), applied to vehicular networks and drug discovery, respectively. The SRD facilitates secure vehicular communication, allowing vehicles to safely change lanes and exit routes without compromising sensitive information. We achieved a 97% improvement in efficiency by significantly reducing communication costs, while incurring a moderate 42% increase in computational cost. The DSP, on the other hand, empowers pharmaceutical companies to collaboratively train a Graph Convolutional Network (GCN) to predict the solubility of drug molecules while fully safeguarding their private datasets. During training, the loss function across all parties averaged 0.0046, while the Mean Squared Error (MSE) on the test set is 1.2, indicating effective model learning. Afterwards, exploiting the quantum computing approach, we propose two novel SMC protocols for Boolean function computation resorting to the Measurement Based Quantum Computing (MBQC) approach and single qubits. We implement the proposed schemes on the IBM Qiskit platform and validate their feasibility.

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Secure Multiparty Computation (SMC) allows multiple individuals, each having their own private data, to perform a computation task without unveiling their data to others. SMC has a wide range of real-life use cases, including machine learning, vehicular networks, banking, defense, and healthcare. However, classical SMC implementations face significant challenges related to both security and efficiency. Classical SMC protocols rely on public-key cryptographic methods, which introduce substantial computational and communication costs. Additionally, these protocols are vulnerable to quantum computer attacks that have the potential to break certain types of cryptographic ciphers, notably those used in RSA. In this thesis, we tackle these challenges by enhancing the security and efficiency of SMC implementations through quantum communication and quantum computing. Quantum communication contributes to enhancing security, while quantum computing, by leveraging quantum processors, offers the potential to significantly improve efficiency. In the quantum communication approach, we propose a Quantum SMC (QSMC) framework that leverages three advanced quantum communication technologies - Quantum Random Number Generation (QRNG), Quantum Key Distribution (QKD), and Quantum Oblivious Key Distribution (QOKD)—in conjunction with a Key Management System (KMS) and the Faster Malicious Arithmetic Secure Computation with Oblivious Transfer (MASCOT) protocol. Exploiting the proposed framework, we implement two essential SMC use cases: Safe Route Departure (SRD) and Drug Solubility Prediction (DSP), applied to vehicular networks and drug discovery, respectively. The SRD facilitates secure vehicular communication, allowing vehicles to safely change lanes and exit routes without compromising sensitive information. We achieved a 97% improvement in efficiency by significantly reducing communication costs, while incurring a moderate 42% increase in computational cost. The DSP, on the other hand, empowers pharmaceutical companies to collaboratively train a Graph Convolutional Network (GCN) to predict the solubility of drug molecules while fully safeguarding their private datasets. During training, the loss function across all parties averaged 0.0046, while the Mean Squared Error (MSE) on the test set is 1.2, indicating effective model learning. Afterwards, exploiting the quantum computing approach, we propose two novel SMC protocols for Boolean function computation resorting to the Measurement Based Quantum Computing (MBQC) approach and single qubits. We implement the proposed schemes on the IBM Qiskit platform and validate their feasibility.
Quantum Secure Multiparty Computation (QSMC) is a technology that takes the advantage of quantum features allowing multiple parties to communicate in a secure and efficient manner while preserving their privacy. Using QSMC technology, we implement a collision warning use case in which vehicles can freely broadcast information while preserving the privacy of their confidential data. We integrate two quantum technologies namely Quantum Key Distribution (QKD) and Quantum Oblivious Key Distribution (QOKD) with the Malicious Arithmetic Secure Computation with Oblivious Transfer (MASCOT) protocol to implement a secure and efficient QSMC platform. This quantum approach significantly improves efficiency and security when we compare it with the classical implementation as both used quantum technologies (QKD and QOKD) are robust against quantum computer attacks.
The development of an efficient quantum computer with enough qubits will benefit humanity, but it will also pose a threat to most public cryptography. Even information secured by public cryptography primitives before the advent of this quantum computer falls under this threat since large quantities of data can be eavesdropped and stored by a malicious actor in hopes of someday having access to a quantum computer that will enable the compromising of the data. PQC and QKD are the main answers to this threat. Even though PQC algorithms aim to transition the existing PKI to be quantum-safe, they still offer the same security guarantees as today’s algorithms offer under a classical setting but rely on a new set of mathematical problems believed not to be vulnerable to a quantum computer. PQC is considered by many to be the main solution for most use cases because its integration carries little to no monetary costs, it calls for no major infrastructure updates, and it can be applied to all applications of public cryptography such as key exchanges and digital signatures. On the other hand, QKD leverages the fundamental laws of quantum mechanics to securely distribute cryptographic keys between remote parties. This solution offers information theoretical security and enables perfect forward secrecy, but it demands the development of a whole new type of network, a QKDN, to normalize the generation, distribution, and usage of quantumgenerated symmetric and oblivious keys. This dissertation presents the approach, implementation, and discussion of two quantum-enabled hybrid services, one applied for secure communications, and the other for secure computations. While the main focus was on the integration of quantum-generated keys into these services, PQC, and classical cryptography were also leveraged as recommended by EU’s commission. Regarding secure communications, a key rotator was developed showing how an existing highly deployed VPN solution can be quantum-enabled in a non-intrusive manner with zero downtime and no performance impact. Regarding secure computations, it was explored how quantum-generated oblivious keys can be leveraged in existing OT-based SMC protocols, integrating the solution into an opensource SMC library, its usage in an SMC service infrastructure, and showcased in the scope of two use cases in the fields of medicine and defense. These services were used in the context of a 5-node test network deployed in Aveiro leveraging both research and commercial QKD Modules, demonstrating the viability of the solutions.
Abstract Secure Multiparty Computation (SMC) enables multiple parties to cooperate securely without compromising their privacy. SMC has the potential to offer solutions for privacy obstacles in vehicular networks. However, classical SMC implementations suffer from efficiency and security challenges. To address this problem, two quantum communication technologies, Quantum Key Distribution (QKD) and Quantum Oblivious Key Distribution were utilised. These technologies supply symmetric and oblivious keys respectively, allowing fast and secure inter‐vehicular communications. These quantum technologies are integrated with the Faster Malicious Arithmetic Secure Computation with Oblivious Transfer (MASCOT) protocol to form a Quantum Secure Multiparty Computation (QSMC) platform. A lane change service is implemented in which vehicles broadcast private information about their intention to exit the highway. The proposed QSMC approach provides unconditional security even against quantum computer attacks. Moreover, the communication cost of the quantum approach for the lane change use case has decreased by 97% when compared to the classical implementation. However, the computation cost has increased by 42%. For open space scenarios, the reduction in communication cost is especially important, because it conserves bandwidth in the free‐space radio channel, outweighing the increase in computation cost.
We analyse a Secure Multiparty Computation (SMC) system assisted with quantum communication technologies. This SMC system is designed to compute phylogenetic trees of SARS-CoV-2 genomes. It adapts a distance-based method known as the Unweighted Pair Group Method with Arithmetic mean (UPGMA) algorithm into a private setting where the sequences owned by each party are not disclosed to the other members present in the protocol. Our main contribution lies on the integration of two quantum communication systems (quantum oblivious transfer and quantum key distribution) with libScapi implementation of the Yao secure computation protocol. This system significantly improves security when compared to its classical implementation since both quantum oblivious transfer and quantum key distribution modules are robust under a quantum computer attack. This system is designed to be compatible with current quantum networks.
Secure multiparty computation (SMC) allows a set of parties to jointly compute a function on private inputs such that, they learn only the output of the function, and the correctness of the output is guaranteed even when a subset of the parties is controlled by an adversary. SMC allows data to be kept in an uncompromisable form and still be useful, and it also gives new meaning to data ownership, allowing data to be shared in a useful way while retaining its privacy. Thus, applications of SMC hold promise for addressing some of the security issues information-driven societies struggle with. In this thesis, we implement two SMC protocols. Our primary objective is to gain a solid understanding of the basic concepts related to SMC. We present a brief survey of the field, with focus on SMC based on secret sharing. In addition to the protocol im- plementations, we implement circuit randomization, a common technique for efficiency improvement. The implemented protocols are run on a simulator to securely evaluate some simple arithmetic functions, and the round complexities of the implemented protocols are compared. Finally, we attempt to extend the implementation to support more general computations.
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))((n, n))((n,n)) threshold approach, requiring the participation of all (n)(n)(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)(\mathcal{B}\approx2.8)(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.