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International Conference on Computational Intelligence and Software Engineering (CiSE)

Research on Secure Scalar Product Protocol and Its' Application

Fen Xu, Shuai Zeng, Shoushan Luo, Cong Wang, Yang Xin, Yucui Guo

Published Sep 1, 2010• 8 citations
Publisher

Abstract

Secure scalar product protocol is an important fundamental protocol in secure multi-party computation. Serving as a basic building block for many other secure protocols, it is widely used in data mining, statistical analysis and scientific computation. Based on additive homomorphism public key cryptosystem, we develop a new secure scalar product protocol under semi-honest model with low communication complexity which is easy to implement and understanding. Furthermore, we firstly apply it to position relationship decision for privacy preserving space vectors.

DOI
10.1109/wicom.2010.5601452

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Secure scalar product protocol is an important fundamental protocol in secure multi-party computation. Serving as a basic building block for many other secure protocols, it is widely used in data mining, statistical analysis and scientific computation. Based on additive homomorphism public key cryptosystem, we develop a new secure scalar product protocol under semi-honest model with low communication complexity which is easy to implement and understanding. Furthermore, we firstly apply it to position relationship decision for privacy preserving space vectors.
Secure multi-party computation with its applications is an important direction in current cryptography research field. The research focuses on how to accomplish the secure cooperative computation among multi-party without the participation of the third party. The two-party bargaining protocol, based on homomorphic public key cryptosystem, was an example of secure multi-party computation's applications. One participant can make a bargain with the other by implementing the protocol. During the implementation of protocol, the privacy of input and the correctness of output could be preserved. The protocol can be implemented without the participation of the third party and its security was based on additive homomorphic public key cryptosystem.
Scalar product protocol and privacy preserving add to multiply protocol (PPAtMP) are two significant basic secure multiparty computation protocols. In this paper, we claim that the two protocols are equivalent to each other and we can achieve one based on the other with the same communication and computation complexity. Then, we propose Secure Two-party Mean Protocol, Secure Shared x ln x Protocol and Secure Shared Generic Polynomial Protocol based on scalar product protocol and PPAtMP. Additionally, we analyze the correctness, security, communication overheads and computation complexity of each protocol proposed in this paper.
A secure multiparty number-product protocol is an important building block in the area of secure multiparty computation. With proper composition of the building block, most applications, such as circuit evaluation, data mining, and private information retrieval, can be executed securely and collaboratively by potentially dishonest parties. In this work, we propose a commodity-based secure number-product protocol, the security of which has been validated with the metrics proposed by Chiang et al. based on information theory. We prove that the protocol can be executed securely under the assumption of semi-honest behavior. Furthermore, if an extra semi-trusted party exists, the proposed protocol can resist any number of corrupt parties. In addition to the security issue, we compare the protocol's communication and computation costs with those of the theoretically secure solution proposed by Ben-Or et al.
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.
Abstract With the rapid development of distributed collaborative computing, privacy leakage risks in multi-source data joint analysis are increasing, and classical secure scalar product (SSP) protocols are vulnerable to quantum attacks. Existing quantum secure scalar product schemes mostly rely on complex quantum resources or third parties, only support two-party computation, and have poor scalability. To address these issues, this paper proposes a secure multi-party quantum scalar product protocol based on single-photon resources without a third party. The protocol adopts a two-layer architectural design, integrating pairwise secure product operation and privacy-preserving aggregation mechanism. It realizes result blinding via data splitting and reconstruction to fully guarantee data confidentiality. By adopting ring interaction structure and lightweight secure computing modes, it completes collaborative computation of multi-party private data and effectively prevents information leakage in interactive processes. Performance analysis shows that the protocol requires no more than single-photon and single-particle measurements, with complexity within a reasonable range, making it feasible with current quantum technology. This protocol provides an efficient and secure primitive for multi-party privacy-preserving collaborative computing in quantum-resistant scenarios.
Secure computation of scalar product is of considerable importance due to its central role in many practical computation scenarios with privacy and security requirements. This paper includes new results about the secure two-party scalar product. Specifically, a perfectly secure and universally composable two-party split scalar product (SSP) protocol is proposed in the preprocessing model. In addition to full security, the proposed SSP protocol enjoys the advantage of optimal efficiency. To show the optimality of this SSP protocol, information theoretic lower bounds on the amount of communicated data in a secure two-party computation in the preprocessing model are derived. These bounds are not limited to SSP functionality but apply to a large class of two-party functionalities. A part of this paper is devoted to applications of the proposed SSP protocol in secure cloud computing. Specifically, based on this protocol, a cloud-assisted privacy-preserving profile-matching scheme and a secure remote health monitoring scheme are proposed. Both of the solutions are highly efficient and significantly improve the previous work.