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.
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.
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 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.
Privacy is ultimately important, and there is a fair amount of research about it. However, few empirical studies about the cost of privacy are conducted. In the area of secure multiparty computation, the scalar product has long been reckoned as one of the most promising building blocks in place of the classic logic gates. The reason is not only the scalar product complete, which is as good as logic gates, but also the scalar product is much more efficient than logic gates. As a result, we set to study the computation and communication resources needed for some of the most well-known and frequently referred secure scalar-product protocols, including the composite-residuosity, the invertible-matrix, the polynomial-sharing, and the commodity-based approaches. Besides the implementation remarks of these approaches, we analyze and compare their execution time, computation time, and random number consumption, which are the most concerned resources when talking about secure protocols. Moreover, Fairplay the benchmark approach implementing Yao's famous circuit evaluation protocol, is included in our experiments in order to demonstrate the potential for the scalar product to replace logic gates.
Secure multiparty computation is a very important research topic in cryptography. The sub-problem of secure multiparty computation that has received special attention by researchers because of its close relation to many cryptographic tasks is secure two-party computation. This area of research is concerned with the question: ldquoCan two party computation be achieved more efficiently and under weaker security assumptions than general multiparty computation?rdquo Yaopsilas protocol provided security against passive adversaries, while Lindell and Pinkas proposed secure two party protocols that are secure against active adversaries. In this paper, we would like to propose a set of information theoretically secure protocols based on scalar product protocol. The detailed complexity analysis is also provided.
There is a fair amount of research about privacy, but few empirical studies about its cost have been conducted. In the area of secure multiparty computation, the scalar product has long been reckoned as one of the most promising alternatives to classic logic gates. The reason for this is that the scalar product is not only complete, which is as good as logic gates, but also much more efficient than logic gates. As a result, we set out to study the computation and communication resources needed for some of the most well-known and frequently referenced secure scalar product protocols, including the composite residuosity, the invertible matrix, the polynomial sharing, and the commodity-based approaches. In addition to the implementation details of these approaches, we analyze and compare their execution time, computation time, and memory and random number consumption. Moreover, Fairplay, the benchmark approach that implements Yao's circuit evaluation protocol, is also included in our experiments in order to demonstrate the potential for the scalar products to replace logic gates.
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.