CN-122027123-A - Multi-party multi-data summation method based on d-dimensional cluster state

CN122027123ACN 122027123 ACN122027123 ACN 122027123ACN-122027123-A

Abstract

The invention relates to the technical field of quantum security computation, and discloses a multi-party multi-data summation method based on d-dimensional cluster state, which introduces a semi-honest third party to assist in completing summation computation and utilizes a double one-way hash function to construct a bidirectional identity authentication process between a participant and the third party so as to effectively prevent identity impersonation attack. In the multipartite multi-data summation stage, a multipartite quantum information interaction structure is established by utilizing quantum entanglement association between d-dimensional Bell states and d-dimensional cluster states, and the safety coding and aggregation of the private data of the participants are realized through Bell measurement. Meanwhile, detection particles from d+1 groups of complementary groups are randomly inserted into the quantum channel and used for detecting potential eavesdropping behaviors and guaranteeing the safety of a quantum communication process.

Inventors

FU KAI
JIANG MIN
ZHOU LIULEI
CHEN HONG
LIU LINA

Assignees

苏州大学

Dates

Publication Date: 20260512
Application Date: 20260415

Claims (10)

1. The multi-party multi-data summation method based on d-dimensional cluster state is characterized by being applied to a quantum channel comprising N participants and a semi-trusted third party, wherein the N participants all have private keys, private bit strings and L groups of two-dimensional Bell states, the semi-trusted third party has public keys, L groups of two-dimensional Bell states and L groups of d-dimensional cluster states, and the method comprises the following steps: Generating an initial ordered sequence containing L elements based on cluster state marking particles for representing the L groups of d-dimensional cluster states of a semi-trusted third party, extracting particles with the same sequence marking to form an element, and constructing a first ordered sequence containing N elements; The semi-trusted third party randomly inserts a plurality of security detection particles into each element of the first ordered sequence to obtain a second ordered sequence, and sends the second ordered sequence to each participant; The semi-trusted third party publishes the insertion position and the measurement base of the safety detection particles used when the second ordered sequence is constructed, so that each participant rejects the safety detection particles in the received second ordered sequence, and restores the safety detection particles to obtain a third ordered sequence; If the error rate between the third ordered sequence and the second ordered sequence of any participant is not greater than a preset threshold, the participant constructs participant marking particles representing the private bit strings of the participant, and brings the participant marking particles into an L group of two-dimensional Bell states of the participant marking particles; the participant builds a private key marking particle for representing the private key of the participant, performs d-dimensional Bell state measurement on the cluster state marking particle and the participant marking particle in the L-group d-dimensional cluster state, acquires a fourth ordered sequence, and transmits the fourth ordered sequence back to a semi-trusted third party; a semi-trusted third party builds third party marked particles for representing the public key, and d-dimensional Bell state measurement is carried out on the third party marked particles and the particles in the fourth ordered sequence to obtain a fifth ordered sequence; and the semi-trusted third party eliminates the sum of the third party marked particles in the fifth ordered sequence, and obtains the summation result of the private bit strings of N participants.
2. The d-dimensional cluster-based multiparty multi-data summation method according to claim 1, wherein based on the cluster-state labeling particles characterizing the L groups of d-dimensional clusters of semi-trusted third parties, an initial ordered sequence comprising L elements is generated, expressed as: ; Extracting particles with identical sequence tags to form an element A first ordered sequence comprising N elements is constructed, expressed as: ; Wherein, the Represents the state of the d-dimensional cluster, Represent the first First of all participants The group d-dimension is in a clustered state, , 。
3. The d-dimensional cluster-based multipartite multi-data summation method according to claim 1, wherein the security detection particles are randomly prepared from d+1 sets of complementary groups including Z, X and iY groups.
4. The d-dimensional cluster-based multiparty multi-data summation method according to claim 1, wherein if the error rate between the third ordered sequence and the second ordered sequence of the participants is greater than a preset threshold, then the quantum channel is eavesdropped, ending the communication.
5. The d-dimensional cluster-state-based multipartite multi-data summation method according to claim 1, wherein the participant performs d-dimensional Bell state measurements on cluster-state labeling particles and participant-labeling particles in the L-group d-dimensional cluster states to obtain a fourth ordered sequence Expressed as: ; Wherein, the Represent the first Private bit string of each participant Bits of The corresponding party marks the particle and, ; Represent the first The first party is at Cluster state marking particles corresponding to the dimensions; representing d-dimensional Bell state measurements.
6. The d-dimensional cluster-state-based multipartite multi-data summation method according to claim 5, wherein a semi-trusted third party builds third party tagged particles characterizing public keys, performs d-dimensional Bell state measurements with particles in a fourth ordered sequence, obtains a fifth ordered sequence Expressed as: ; Wherein, the Is the first The first party is at Utility-corresponding public key Is a third party to the marking of particles, 。
7. The d-dimensional cluster state-based multiparty multi-data summation method according to claim 1, wherein obtaining summation results of the private bit strings of the N participants comprises summing values on the same bit in the private bit strings of the N participants, obtaining a numerical sum corresponding to each bit, and accumulating to obtain summation results.
8. The d-dimensional cluster-based multi-party multi-data summing method according to claim 1 further comprising authenticating the N participants before multi-party multi-data summing, each participant comprising: selecting a random number, and calculating and acquiring an identity hash value based on a public key and a private key owned by the public key; Selecting a key from the system key parameter sequence based on the random number to serve as a secondary hash key; acquiring an initial element sent by a semi-trusted third party and an identity verification code with the length of L-2; Based on the random number, the initial element and the secondary hash key, calculating and acquiring a first hash function and a second hash function, and sending the first hash function and the second hash function to a semi-trusted third party, so that the semi-trusted third party calculates and acquires a third hash function and a fourth hash function based on the participant, the random number and the secondary hash key; if the third hash function is equal to the first hash function and the fourth hash function is equal to the second hash function, the participant performs multiparty data summation through security verification, otherwise, the participant does not pass the security verification.
9. The d-dimensional cluster-based multiparty multi-data summation method according to claim 8, wherein the first hash function is computed based on random number, initial element and secondary hash key With a second hash function Expressed as: ; ; Wherein, the Expressed in terms of 、 And (3) with As a secondary hash function of the key, Expressed in terms of And (3) with A second-level hash function for the key; Representing a sequence of system key parameters; representing a one-way hash function taking a system key parameter sequence as a key; Represent the first The identity verification code of the individual party, Represent the first The random number of the individual party, The initial element is represented as such, Represent the first Secondary hash keys of the individual participants.
10. The d-dimensional cluster-based multiparty multi-data summation method according to claim 9, wherein semi-trusted third party calculates and obtains a third hash function based on the participant and its random number, the second hash key With a fourth hash function Expressed as: ; 。

Description

Multi-party multi-data summation method based on d-dimensional cluster state Technical Field The invention relates to the technical field of quantum security computation, in particular to a multi-party multi-data summation method based on d-dimensional cluster state. Background Under the background that the security and high-efficiency data aggregation is needed in privacy calculation, quantum cryptography based on the quantum mechanics principle is generated, the dependence of classical cryptography on algorithm complexity is broken, and unconditional security in the information theory layer is ensured by virtue of a physical law. Since the pioneering work of quantum cryptography was proposed in Bennett and Brassard in 1984, quantum communication technology has undergone a crossover from theoretical exploration to application explosion. At present, various application forms such as Quantum Key Distribution (QKD), quantum Security Direct Communication (QSDC), quantum multiparty summation and the like are widely applied, which not only marks the trend of the maturity of quantum cryptography, but also predicts the acceleration of the formation of a quantum security network system. Secure Multiparty Computing (SMC) is an important branch in cryptography, which implements data computation in a way that protects user privacy. The main goal of Secure Multiparty Computing (SMC) is to enable n mutually untrusted parties to co-compute a function while maintaining the confidentiality of the respective inputs. Secure multiparty computation was proposed by Yao in 1982, which allows n participants to jointly compute a function of their private inputs and to secure each participant's private input. Among them, secure Quantum Summation (SQS) is an important and interesting part thereof, since it can sum a certain amount of input data to obtain correct results, while still unconditionally preserving their confidentiality, which is of great importance in the field of privacy protection. Secure multiparty summation (SQS) is known to be a fundamental primitive of Secure Multiparty Computation (SMC) and can be used to build complex security protocols for other multiparty computation. The existing secure multiparty summation is based on traditional cryptography, and has high computational complexity, low summation efficiency and risk of revealing privacy data of participants. Disclosure of Invention Therefore, the technical problem to be solved by the invention is to solve the problem that the privacy of multiparty data cannot be effectively protected in the prior art. In order to solve the technical problems, the invention provides a multi-party multi-data summation method based on a d-dimensional cluster state, which is applied to a quantum channel comprising N participants and a semi-trusted third party, wherein the N participants all have private keys, private bit strings and L groups of two-dimensional Bell states, the semi-trusted third party has public keys, L groups of two-dimensional Bell states and L groups of d-dimensional cluster states, and the method comprises the following steps: Generating an initial ordered sequence containing L elements based on cluster state marking particles for representing the L groups of d-dimensional cluster states of a semi-trusted third party, extracting particles with the same sequence marking to form an element, and constructing a first ordered sequence containing N elements; The semi-trusted third party randomly inserts a plurality of security detection particles into each element of the first ordered sequence to obtain a second ordered sequence, and sends the second ordered sequence to each participant; The semi-trusted third party publishes the insertion position and the measurement base of the safety detection particles used when the second ordered sequence is constructed, so that each participant rejects the safety detection particles in the received second ordered sequence, and restores the safety detection particles to obtain a third ordered sequence; If the error rate between the third ordered sequence and the second ordered sequence of any participant is not greater than a preset threshold, the participant constructs participant marking particles representing the private bit strings of the participant, and brings the participant marking particles into an L group of two-dimensional Bell states of the participant marking particles; the participant builds a private key marking particle for representing the private key of the participant, performs d-dimensional Bell state measurement on the cluster state marking particle and the participant marking particle in the L-group d-dimensional cluster state, acquires a fourth ordered sequence, and transmits the fourth ordered sequence back to a semi-trusted third party; a semi-trusted third party builds third party marked particles for representing the public key, and d-dimensional Bell state measurement is carried out on the third part