Secure multiparty computation is a basic cryptographic primitive that has many important applications in privacy preservation. In this work, we propose a new secure multiparty computation protocol for the maximum and minimum values based on quantum homomorphic encryption. Owing to the speciality of quantum homomorphic encryption, participants can delegate a server to compute the maximum and minimum values of their private data. Furthermore, both calculations are performed on the encrypted data, and therefore the privacy of their respective private data can be perfectly guaranteed.
Secure multiparty computation is a basic cryptographic primitive that has many important applications in privacy preservation. In this work, we propose a new secure multiparty computation protocol for the maximum and minimum values based on quantum homomorphic encryption. Owing to the speciality of quantum homomorphic encryption, participants can delegate a server to compute the maximum and minimum values of their private data. Furthermore, both calculations are performed on the encrypted data, and therefore the privacy of their respective private data can be perfectly guaranteed.
The significant advantage of the quantum homomorphic encryption scheme is to ensure the perfect security of quantum private data. In this paper, a novel secure multiparty quantum homomorphic encryption scheme is proposed, which can complete arbitrary quantum computation on the private data of multiple clients without decryption by an almost dishonest server. Firstly, each client obtains a secure encryption key through the measurement device independent quantum key distribution protocol and encrypts the private data by using the encryption operator and key. Secondly, with the help of the almost dishonest server, the non-maximally entangled states are pre-shared between the client and the server to correct errors in the homomorphic evaluation of T gates, so as to realize universal quantum circuit evaluation on encrypted data. Thirdly, from the perspective of the application scenario of secure multi-party computation, this work is based on the probabilistic quantum homomorphic encryption scheme, allowing multiple parties to delegate the server to perform the secure homomorphic evaluation. The operation and the permission to access the data performed by the client and the server are clearly pointed out. Finally, a concrete security analysis shows that the proposed multiparty quantum homomorphic encryption scheme can securely resist outside and inside attacks.
Secure multi-party computation has been playing a fundamental role in terms of classical cryptography. Quantum homomorphic encryption (QHE) could compute the encrypted data without decryption. At present, most protocols use a semi-honest third party (TP) to protect participants’ secrets. We use a quantum homomorphic encryption scheme instead of TP to protect the privacy of parties. Based on quantum homomorphic encryption, a secure multi-party quantum summation scheme is proposed in which N participants can delegate a server with strong quantum computing power to assist computation. By delegating the computation and key update processes to a server and a semi-honest key center, participants encrypt their private information data using Pauli operators to get the sum. Besides, the server can design and optimize the summation lines itself, and the correct results can be obtained even if the secret information is negative. The correctness analysis showed that the participants could correctly obtain the results of the calculation. The security analysis proves the scheme is resistant to both outside attack and participant’s attack, and is secure against collusive attack by up to N-2 participants. From the theoretical point of view, our protocol can extend to other secure multi-party computing problems.
Secure multiparty computation is valuable for studying data privacy protection issues due to its decentralization, input privacy, fairness, etc. One of the most fundamental problems is to confidentially compute the maximum and the minimum of multiple data. In this paper, an efficient secure multipart computation scheme that can compute the maximum and the minimum simultaneously without a trusted third party was proposed to address the problems of existing secure multi-party computation protocols, such as inability of computing the maximum and the minimum at one time, low efficiency, and security risks caused by unique designated decryption key holder. In the scheme, an encoding method that can simultaneously compute the maximum and the minimum was first provided, whose basic idea was to give a complete set of ordinal numbers with potential l (l ≥ the number of participants n), and each participant encodes its data into an array with length l where the location of the data in the complete set was coded as a random number and the other positions were coded as 1. The positions of the leftmost and rightmost non-1 values in the product array were the positions of the maximum and minimum in the whole set. Based on the proposed encoding method, the ElGamal homomorphic encryption algorithm was used to guarantee the confidentiality of all participants’ data, and the maximum threshold decryption was used to make each participant hold part of the decryption key, which avoids the security threats caused by centralized decryption of calculation result by designated key holder. The proposed scheme was proven to be resistant to collusive attacks by any participant under a semi-honest model based on an ideal-realistic simulation paradigm. Finally, the efficiency analysis and performance comparison with related maximum (minimum) computing schemes were given, which showed that the proposed protocol has advantages over existing schemes in terms of computational complexity and communication complexity under the premise of higher security.
Threshold private set intersection is a basic primitive of secure multiparty computation, which has many important applications in the field of privacy preservation and information security, especially in a ride sharing system, one of the most transforming and innovative technologies enabled by the Internet of Things. In this paper, we propose a new proposal for threshold private set intersection based on quantum homomorphic encryption, in which both the number of users and the designated trusted party are flexible. Furthermore, the complicated computing task can be delegated to a server for processing contributing to the speciality of quantum homomorphic encryption. More importantly, the users’ privacy is perfectly guaranteed because all the calculations are performed on the quantum encrypted data. Therefore, this proposal is more practical compared with the prior work.
Secure multiparty computation is a key privacy-preserving technology in cyberspaces and a research focus in the international cryptographic community.We first present a new encoding scheme to encode private data.By using this encoding scheme together with homomorphic encryption scheme,we construct a new scheme for Yao′s millionaires′ problem and prove its privacy-preserving property.This new scheme is more concise,more general and can be applied to compare any two objects on which a total order can be defined.We finally utilize the new scheme to propose a solution to the coprime problem and prove the privacy-preserving properties of the solution.
Abstract Quantum computers promise not only to outperform classical machines for certain important tasks, but also to preserve privacy of computation. For example, the blind quantum computing protocol enables secure delegated quantum computation, where a client can protect the privacy of their data and algorithms from a quantum server assigned to run the computation. However, this security comes with the practical limitation that the client and server must communicate after each step of computation. A practical alternative is homomorphic encryption, which does not require any interactions, while providing quantum-enhanced data security for a variety of computations. In this scenario, the server specifies the computation to be performed, and the client provides only the input data, thus enabling secure noninteractive computation. Here, we demonstrate homomorphic-encrypted quantum computing with unitary transformations of individual qubits, as well as multi-qubit quantum walk computations using single-photon states and non-birefringent integrated optics. The client encrypts their input in the photons’ polarization state, while the server performs the computation using the path degree of freedom. Our demonstration using integrated quantum photonics underlines the applicability of homomorphic-encrypted quantum computations, and shows the potential for delegated quantum computing using photons.