3320 results about "Quantum computer" patented technology

The AI-enhanced cellular modeling and simulation platform is a computational system designed to enhance biomedical research and development and personalized medicine and wellness. This platform integrates simulation modeling, machine learning and artificial intelligence, multi-omics data, and sophisticated data fusion and decision-support techniques to create comprehensive models of cellular systems and processes across multiple scales. It enables researchers and clinicians to simulate complex biological interactions, predict disease progression, and design or optimize treatment strategies or medical devices with improved accuracy and efficacy. The system's architecture allows for integration of various components, including real-time data processing, federated learning, and quantum computing enhancements. From personalized drug discovery and cancer therapies to synthetic biology and epidemiological analysis, this platform offers powerful tools for understanding and manipulating cellular systems and bioengineered systems. By bridging the gap between molecular-level interactions between cells and materials and organism-wide effects, it enables significant advancements in healthcare and biological sciences.

The invention relates to the technical field of document retrieval and information processing in the data processing technology, in particular to a document retrieval method based on multistage indexing and feature clustering, which comprises the following steps: performing high-dimensional space mapping on multi-modal features such as texts and images through a quantum embedding layer to generate cross-modal joint feature representation; a first-level index of a multi-level index architecture is dynamically initialized based on a meta-clustering algorithm, and semantic blocks of a second-level index are divided in combination with a multi-head self-attention mechanism. And an optimal transmission matrix is generated by using a Sinkhorn algorithm to align cross-node feature distribution. The multi-target mixed retrieval strategy is fused with vector retrieval, keyword retrieval and graph retrieval results, and weight distribution is dynamically adjusted. Through collaborative optimization of quantum calculation, federated learning and causal reasoning, a closed-loop technical architecture from feature analysis to dynamic index construction is formed, the problems of insufficient cross-modal fusion, static clustering deviation and semantic association deficiency are solved, and the precision, efficiency and dynamic adaptability of heterogeneous document retrieval are improved.

The invention relates to a traffic flow prediction optimization method based on an intelligent optimization algorithm, which is applied to the technical field of traffic flow prediction. The system comprises a multi-modal data acquisition and fusion module, a hybrid deep learning prediction module, an intelligent parameter optimization module, an integrated learning module, a multi-scale error correction module, a prediction result analysis and visualization module, a distributed learning and privacy protection module and the like. Wherein the hybrid deep learning prediction module adopts an attention mechanism to fuse models such as CNN, Transform and LSTM, and introduces an adaptive error correction mechanism, so that the prediction precision is remarkably improved; the intelligent parameter optimization module accelerates the model search efficiency by using technologies such as quantum computing and swarm intelligence optimization; the integrated learning module and the adversarial training strategy enhance the robustness and generalization of the model; and the multi-scale error correction module adopts a time sequence decomposition and self-adaptive online learning method to improve the accuracy of long-term and short-term prediction.

The invention relates to the technical field of cloud computing, and discloses a resource scheduling method, device and equipment, and the method comprises the steps: generating a multi-dimensional data topological graph of cloud environment monitoring data, decomposing a to-be-scheduled job set into quantum computing unit sets which can be processed in parallel, and adding priority labels for the quantum computing unit sets through a quantum heuristic algorithm, according to priority labels and a multi-dimensional data topological graph, physical resources of a cloud environment are divided into non-uniform resource fragments matched with task requirements, based on the non-uniform resource fragments, resource scheduling is carried out through an improved hybrid particle swarm optimization algorithm, and weighting and fitness evaluation and resource constraint correction are introduced. According to the resource scheduling method and device, the multi-dimensional data topological graph is generated to comprehensively present the resource state and association, then the to-be-scheduled job set is decomposed into the quantum computing unit sets, the priority labels are added, and then the non-uniform resource fragments are divided for resource scheduling, so that the resource adaptation accuracy is improved, and the scheduling efficiency and the resource utilization rate are improved.

The invention discloses a market supervision data security protection method and system based on a dynamic encryption strategy, and relates to the technical field of information security. The method comprises the following steps: generating an initial seed input improved four-dimensional hyperchaotic system, and generating a dynamic encryption parameter set through chaotic mapping iteration; the method comprises the following steps: carrying out adaptive fragmentation on market supervision data to be encrypted to generate a data sub-block set, carrying out dynamic S-box-based symmetric encryption on odd index sub-blocks, carrying out a chaotic stream encryption mode associated with a current dynamic sub-key on even index sub-blocks, and generating a unique quantum chaotic fingerprint for each encrypted sub-block; a searchable encryption index is jointly constructed by using a post-quantum encryption algorithm and a lattice-based encryption algorithm and is used for carrying out query operation under the condition that data is not decrypted; the encryption security, privacy protection capability and quantum computing attack resistance of the market supervision data are remarkably improved, and meanwhile, an efficient, flexible and extensible data security protection scheme is provided.

Systems and methods are disclosed for optimization, management, and merging of processes. This system integrates a multifaceted technological framework, including generative artificial intelligence, quantum computing simulations, and blockchain technology. It features a user interface for inputting diverse workflow requirements, a generative AI module for processing these inputs, and a quantum computing module for simulating and optimizing workflows. The system utilizes blockchain for secure workflow deployment and a suite of specialized engines for prompt management, data extraction, analysis, optimization, deployment orchestration, and continuous monitoring. These components ensure the system's adaptability to user-specific needs, scalability across various industries, and capability for integration with existing enterprise systems. This invention revolutionizes BPM by streamlining processes, enhancing efficiency, and maintaining high security and customization standards.

The invention discloses a method and a system for determining the reaction activity of material molecules based on quantum computing, and relates to the technical field of material performance analysis based on quantum computing, and the method comprises the following steps: generating UCCSD (Unified Conduction Cathode Spectroscopy) simulation according to an electronic structure of molecules of a target material; obtaining at least one effective excitation operator based on parameters in the coefficient of each excitation operator in UCCSD simulation and by combining all the excitation operators; constructing a quantum circuit according to all the effective excitation operators; determining energy level distribution of molecules of the target material based on the quantum circuit; and determining the reaction activity of the molecules of the target material according to the energy level distribution of the molecules of the target material. According to the method, in the process of obtaining the effective excitation operator, an ADAPT-VQE algorithm does not need to be executed, so that the analysis cost of the physical and chemical properties of the material can be reduced, and the analysis efficiency of the physical and chemical properties of the material can also be improved.

The invention discloses a data annotation method and system of a collaborative computing architecture based on quantum computing, and belongs to the field of data annotation. The method comprises the steps that S1, multi-modal data are input and preprocessed; s2, extracting features of each mode after preprocessing; s3, coding the features of each mode into a quantum state, and carrying out mode fusion; s4, performing label reasoning on the quantum state after modal fusion, and performing label constraint optimization by using a quantum approximate optimization algorithm; s5, based on a quantum Bayesian network or an approximate causal graph generation method, generating explanation according to a modal contribution causal path, and deducing marginal contribution of each modal to final label prediction by using a joint probability measurement result; and S6, outputting a labeling result. According to the method, a quantum-classical cooperative computing architecture is designed, the efficiency and accuracy of multi-modal data labeling are remarkably improved, the interpretability, the distributed processing capacity and the high-dimensional feature modeling capacity of the system are enhanced, and a brand new solution thought is provided for development of the multi-modal labeling technology.

The invention discloses a market supervision data exchange platform migration and security enhancement method and system based on a credential environment, and relates to the technical field of network security. In the data migration process, the consistency and privacy protection of the data are ensured through Hash check and a multi-party security computing technology; a domestic commercial cryptographic algorithm and a quantum resistance encryption technology are introduced, so that the protection capability of the platform to existing security threats is effectively improved, and the resistance to future quantum computing threats is enhanced; an intrusion detection system and a virtual honeypot node are integrated, and a defense strategy is monitored and updated in real time in combination with a deep learning model, so that novel attack behaviors can be detected and coped with in real time; according to an intrusion detection alarm and a block chain audit result, a security policy and resource allocation are dynamically adjusted in combination with a machine learning technology, it is ensured that high-risk nodes are monitored in time, resource allocation is automatically optimized, and the resource utilization efficiency and security of the system are improved.

The invention provides an intelligent lock control method and system based on dynamic identity verification, and relates to the technical field of artificial intelligence, and the method comprises the steps: building a multi-dimensional risk assessment model comprising an operation time interval, a biological characteristic change rate and a spatial position parameter, and obtaining a risk assessment score; according to the risk assessment score, performing preliminary adjustment on the biological characteristic data, and performing encryption processing and characteristic enhancement on the preliminarily adjusted biological characteristic data in combination with a dynamic key to obtain processed biological characteristic data; performing collaborative calibration on the processed biological characteristic data according to the risk assessment score to obtain calibrated biological characteristic data; and encrypting the calibrated biological characteristic data through an anti-quantum computing encryption protocol, and carrying out weighted fusion on the encrypted characteristic data, the dynamic key, the environmental adaptability score and the risk assessment score to generate a final unlocking instruction. According to the invention, the safety and robustness of the intelligent lock are improved.

The invention discloses an image classification method based on an extensible quantum convolutional neural network, and relates to the technical field of image classification, and the method comprises the steps: carrying out the preprocessing of to-be-classified image data, and then carrying out the slicing processing; converting the slice data into quantum state information through angle coding; a quantum system is constructed, the quantum system comprises a quantum feature extraction part and a quantum classification measurement part, the quantum feature extraction part comprises a quantum variational circuit model with a quantum convolutional layer, and the model can perform feature extraction on quantum state information by using alternating single quantum bit gates and double quantum bit gates; training a quantum variational circuit model by using a part of quantum state information; and inputting the other part of quantum state information into the trained quantum variational circuit model, and measuring the output quantum state of the quantum variational circuit model. According to the method, the problems that traditional deep learning is high in computing resource demand, limited in quantum computer scale and the like are solved, and a novel and practical method is provided for efficient image classification.

The invention discloses a cross-regional network fault prevention and repair method, system and device and a medium, and the method specifically comprises the steps: collecting the multi-modal data of a cross-regional network according to distributed monitoring nodes, and generating a multi-modal AI model through the training of the multi-modal data based on a quantum computing platform; deploying the multi-modal AI model to each edge node of a cross-regional network, and performing fault detection on each edge node according to the multi-modal AI model to obtain a fault detection result; according to the fault detection result and the real-time network state of the cross-regional network, dynamically adjusting a traffic scheduling strategy of the cross-regional network through a reinforcement learning algorithm; and determining a fault self-healing strategy according to the fault detection result, and executing a fault self-healing operation on the cross-regional network through the fault self-healing strategy. According to the method, the technical bottleneck faced by a cross-regional network fault prediction and self-healing system is effectively solved, and the real-time performance, the accuracy and the self-adaptive capability of the system are improved.

The invention discloses an excess fusion computing power scheduling system based on a directed acyclic graph and a task processing method. The excess fusion computing power scheduling system comprises a task splitting module, an execution graph generation module and a quantum-classical computing power resource module. The task splitting module is configured to split an input calculation task and determine a plurality of task operators, and the task operators comprise quantum task operators and classic task operators. The execution graph generation module is configured to determine an execution graph based on the directed acyclic graph according to a dependency relationship among the plurality of task operators. And the quantum-classical computing power resource module is configured to determine the task computing power resource allocated to each task operator according to the execution graph so as to process the computing task. Therefore, through the over-fusion computing power scheduling system based on the directed acyclic graph, effective management and scheduling of quantum computing resources and classical computing resources can be realized, the processing time of the computing task is shortened, and the processing efficiency of the computing task and the system performance are improved.

The invention provides a data quality detection and improvement system for a large language model, and relates to the technical field of code quality management. The data analysis and characteristic extraction module is used for extracting structured and semantic characteristics of codes and constructing a code distribution diagram; the multi-dimensional quality detection module comprehensively evaluates the data set quality from three aspects of semantic diversity, structural consistency and error mode; the code optimization and verification module generates an optimization suggestion based on a detection result, and verifies the effectiveness of an optimization scheme through dynamic evaluation and unit testing; the feedback and self-adaptive optimization module is combined with developer feedback and runtime performance test to dynamically adjust a repair strategy, and the complex code repair efficiency is improved through quantum computing auxiliary path search; according to the method, full-process automation from quality detection to optimization verification is achieved, the method is suitable for multi-dependency and multi-module complex code repair tasks, and the quality and efficiency of the code life cycle are improved.

The invention belongs to the technical field of power system simulation application, and particularly relates to a power system simulation optimization method based on data driving. Based on a data-driven dynamic adaptive space-time segmentation and cooperation model, a fast-varying electromagnetic transient process is mapped to a quantum processor, a slow-varying electromechanical transient process is reserved in a classical computer, a power grid node voltage is coded into quantum bit amplitude, a power grid is dynamically equivalent to quantum Hamiltonian, and a quantum Hamiltonian is obtained. And decoupling the quantum domain of the fast-changing electromagnetic transient state and the classical domain of the slow-changing electromechanical dynamic state to realize self-adaptive balance simulation precision and efficiency. Quantum calculation sparse codes and dynamic error correction are constructed, non-uniform code distance distribution is achieved, cross-scale data transmission errors are reduced, high-frequency harmonic distortion is avoided, high fault-tolerant simulation is achieved under limited quantum resources, code distances are dynamically adjusted through reinforcement learning of a DDPG strategy, noise fluctuation and power grid working condition changes are responded in real time, and resources and fault-tolerant balance are optimized.

The invention provides a multi-party collaborative anti-quantum signature method and system based on homomorphic Hash, and relates to the technical field of digital signatures, the system comprises a plurality of participants and a verification party, and the method is specifically as follows: each participant generates a pair of public and private keys, the public key is composed of a total public key, a total signature matrix and a total Hash matrix of all participants; based on the public and private keys, all participants perform multi-party signature on the target message through a homomorphic hash function, and a generated signature is composed of total hash challenge values of all participants, total response vectors of all participants and commitment value high-order difference values of all participants; according to the signature, the verifier recovers the high order of the total commitment value, further calculates the total hash challenge value, and verifies the validity of the signature through comparison of the total hash challenge value; according to the method, multi-user collaborative signature is realized, and the security of resisting malicious opponents under a quantum computer is obtained.

The embodiment of the invention provides an IPSec hybrid anti-quantum computing security method and electronic equipment, and relates to the technical field of communication security, the method comprises the following steps: when a key negotiation request sent by an initiator is received, sending a first key negotiation message to the initiator; receiving a second key negotiation message sent by the initiator; decrypting the received first encrypted information by using a private key corresponding to the encryption certificate of the responder, and decrypting the received second encrypted information to obtain a first anti-quantum encryption public key; packaging the second random key by using the first anti-quantum encryption public key, and encrypting by using the third random key to obtain third encrypted information; encrypting the third random key by using a public key in an encryption certificate of the initiator to obtain fourth encrypted information; and sending a third key negotiation message containing the third encrypted information and the fourth encrypted information to the initiator. According to the scheme, cracking of the key by quantum computing can be resisted.

The invention discloses an anti-quantum security data transmission authentication method based on an SLH-DSA, and aims to cope with communication security challenges in a quantum computing environment. The device generates a key pair locally in a registration phase and applies for an anti-quantum identity certificate from a certificate agent. In the authentication stage, a user exchanges an identity certificate and a key parameter to realize identity authentication and negotiate a shared key. In the data transmission stage, a session key is dynamically derived by using a shared key, data is encrypted in combination with a national secret symmetric encryption algorithm SM4, and integrity verification is performed by using an anti-quantum signature algorithm. The method gives consideration to security, lightweight and performance, has quantum attack resistance and forward security, is suitable for application scenarios with high data security requirements, such as industrial Internet of Things and smart power grids, and has good application prospects and popularization values.

Systems / techniques that facilitate fusion of (or multiplexing) classical computing, artificial intelligence, or quantum computing for vehicle operations are provided. In various embodiments, a system can establish computational intensity thresholds for classical computing, artificial intelligence and quantum computing. In various aspects, the system can engage, through fusion of (or multiplexing) classical computing, artificial intelligence, or quantum computing for a vehicle operation based on the vehicle operation's computational intensity. In various instances, the system can engage classical computing, artificial intelligence or quantum computing in parallel or separately for vehicle operation.

The invention relates to the technical field of information security, in particular to an anti-quantum computing public key cryptography method and system. The method comprises the following steps: acquiring a large prime number p and constructing a multivariable polynomial ring; randomly generating a group of polynomial coefficients, generating a polynomial embedding rule public key, and generating a multivariable polynomial ring embedding public key; the method comprises the following steps: acquiring a quantum computer message, performing polynomial space mapping conversion and message public key encryption, and meanwhile, generating a quantum message public key encrypted ciphertext by introducing a polynomial perturbation term and a transcendental coding term; the quantum message public key encryption ciphertext and the corresponding polynomial ring embedded public key are transmitted to a quantum message decryption party for inversion decryption processing, and a quantum computer message decryption plaintext is generated; and performing anti-quantum computing security analysis on the encryption and decryption processes, and regenerating a multivariable polynomial ring dynamic public key. According to the method, the attack of quantum computing can be effectively resisted, so that the security of quantum information transmission is guaranteed.

The invention discloses a method and system for assimilating meteorological satellite hyperspectral error non-Gaussian distribution data based on quantum computing, and the method carries out the generalized quality control of meteorological satellite hyperspectral data in consideration of an outlier value on the observation brightness temperature and equivalent data of a satellite hyperspectral infrared detector channel. Comprising the steps of channel optimal selection considering quantum information entropy, deviation correction based on artificial intelligence generalized integration generation type deep learning and cloud detection based on a minimum residual method to remove cloud view field point data, so that quality control data is obtained. And performing quantum space solution on the quantum non-Gaussian increment four-dimensional variational assimilation model compatible with error Gaussian distribution and non-Gaussian distribution based on quality control data to obtain analysis field data, and solving the problem that the brightness temperature assimilation of the hyperspectral infrared channel with error non-Gaussian distribution (or obvious non-Gaussian characteristics) is limited in the prior art. Meanwhile, the method is high in solving speed, and the obtained analysis field data has good precision and calculation timeliness.

The invention discloses a digital certificate authentication method and device based on a post-quantum algorithm, equipment and a medium, and relates to the field of information security, and the method comprises the steps: obtaining digital certificate application information of a target entity for auditing; if the digital certificate request passes the verification, analyzing the digital certificate request submitted by the target entity, and obtaining a key encryption key of the digital certificate request by using a post-quantum key encapsulation algorithm after verification; then obtaining user information of the target entity and an active cryptographic algorithm public key value in the digital certificate request, generating an anti-quantum-attack digital certificate according to the user information and a public key, and signing and issuing the anti-quantum-attack digital certificate to the target entity; the digital certificate comprises a post-quantum key packaging public key, a post-quantum signature public key and an active-service public key password public key ciphertext of the entity. According to the application, the public key data of the traditional public key cryptographic algorithm can be protected, the quantum computing attack is resisted, the public key plaintext of the traditional public key cryptographic algorithm can be obtained in the service system, and the influence on the original service using the traditional public key cryptographic algorithm is extremely low.

The invention discloses a data protection method for fusing a quantum key in a TLS, and relates to the technical field of quantum secret communication. According to the method, a quantum key is combined with a pre-shared key to perform identity authentication, and a pre-shared key database is continuously updated, so that the problem that a public key identity authentication system is easily attacked by quantum computing and the problem that the security is reduced due to repeated use of the pre-shared key in the existing method are solved; meanwhile, according to the method, a session key used in the communication process is generated by taking the quantum key as a key material through a preset key generation algorithm, so that the use of an unsafe traditional key exchange algorithm is avoided, and the security of data transmission is enhanced.

The invention relates to the technical field of quantum computers, in particular to an anti-quantum signature method and system used between two terminals and electronic equipment. The initial to-be-verified commitment value of each terminal is obtained by homomorphic Hash commitment operation of the signature calculation result of the public key information stored in the terminal private key and encryption based on the commitment key, so that the confidentiality and randomness of the public commitment value are effectively ensured, and only two terminals need to interact and share the initial to-be-verified commitment value in the process. Compared with conventional data encryption, transmission and decryption operations, the data transmission frequency is reduced, and the signature verification effect is improved.

The embodiment of the invention discloses a cooperative signature method and a related device, and the method comprises the steps: a mobile terminal calculates a middle elliptic curve point according to a first random number and an elliptic curve base point, and transmits the middle elliptic curve point to a cooperative terminal, the cooperation end calculates a final elliptic curve point according to the intermediate elliptic curve point, the second random number, a sub-private key of the cooperation end and an elliptic curve base point, calculates a final target signature validity verification message and an intermediate target signature integrity verification message according to the final elliptic curve point, and sends the information to the mobile end; and the mobile terminal calculates a final target signature integrity verification message according to the private key of the mobile terminal, the first random number, the final target signature validity verification message and the intermediate target signature integrity verification message, and takes the final target signature validity verification message, the integrity verification message and the Diithium signature as the target signature. By adopting the embodiment of the invention, the protection capability of the private key can be improved, and meanwhile, the resistance of the system to future quantum computing threats is enhanced.

The invention discloses a mobile communication method based on anti-quantum and national cryptographic algorithm mixing and a mobile terminal. The method comprises the steps that the mobile terminal generates a first mixed verification public key and a first mixed signature private key; obtaining a mixed signature certificate; the mobile terminal obtains the mixed ciphertext and the first symmetric key, and the mobile terminal signs the mixed ciphertext to obtain a mixed signature; the validity of the hybrid signature certificate is verified by the server side by using a second hybrid verification public key, the validity of the hybrid signature is verified by a first hybrid verification public key built in the hybrid signature certificate, and the hybrid signature is decrypted by the server side by using a second hybrid decryption private key to obtain a first symmetric key; and the mobile terminal and the server side perform encryption communication by using the first symmetric key. Compared with the prior art, the mobile communication method based on the anti-quantum and national cryptographic algorithm mixture provided by the invention ensures the secure communication between the client and the server, and can maintain the confidentiality and integrity of data even under the threat of quantum computing.

The invention provides an anonymous Internet of Things identity authentication method and device based on an anti-quantum computing password. A key generation device sends a public key to a message sending end and a message receiving end, and sends a private key to an authentication server; the authentication server generates a blind parameter based on the private key, and sends the blind parameter to the message sending end; the message sending end performs blind operation based on the blind parameter, the public key and the to-be-transmitted message to obtain a blind message, and sends the blind message to the authentication server; the authentication server performs post-quantum signature on the blind message based on the private key to obtain a to-be-solved blind signature, and sends the to-be-solved blind signature to the message sending end; the message sending end carries out blind resolution operation on the to-be-resolved blind signature to obtain a target signature; the message sending end sends the to-be-transmitted message and the target signature to a message receiving end; and the message receiving end performs post-quantum verification on the target signature based on the public key, and if verification succeeds, processing is performed based on the to-be-transmitted message. Through the scheme of the invention, the user data security can be improved.

The invention relates to the technical field of network communication security, and discloses a real-time encrypted transmission network communication security guarantee system, which comprises a dynamic fragmentation quantum resistance encryption module, a flow perception-based adaptive encryption engine, a zero-handshake continuous identity authentication module and a hardware acceleration fragmentation processing architecture, and the dynamic fragmentation quantum resistance encryption module is configured to segment a data stream into a plurality of fragments according to a time window, and independently generate an unassociated key for each fragment based on a quantum security NTRU algorithm. According to the network communication security guarantee system for real-time encryption transmission, the traditional network communication security guarantee technology is comprehensively innovated, and the problems of static key management, encryption algorithm adaptation, data fragmentation encryption, identity authentication and encryption cooperation, quantum computing threat response and the like are successfully solved; and the performance of the system in key performance dimensions such as security, real-time performance, adaptability, reliability and anti-attack capability is obviously improved.

The invention discloses a quantum computer and super computer connection fusion method, which comprises the following steps of: constructing a quantum computer architecture and a super computer architecture, and realizing connection between the quantum computer architecture and the super computer architecture through a hardware layer; inputting the calculation data into a super computer, and performing task classification on the calculation data by utilizing an innovation fusion module to obtain a plurality of calculation tasks; utilizing an AI model to predict execution time and resource consumption of the plurality of calculation tasks on the quantum computer and the super computer respectively, and adjusting the distribution proportion of the plurality of calculation tasks on the quantum computer and the super computer; and transmitting the calculation data to the super computer and the quantum computer for classical calculation and quantum calculation according to the distribution proportion, and transmitting a calculation result back to a central node of the super computer to complete a calculation task. The invention relates to the field of quantum computing and high-performance computing, and solves the technical problem that the computing efficiency is low when a quantum computer and a super computer are used for computing in the prior art.

The invention discloses a federated learning method based on quantum transfer learning, relates to the cross technical field of quantum computing and federated learning, and aims to solve the problem of performance bottleneck of traditional federated learning under non-independent identically distributed data. The local model of each client is fused with a classic convolutional layer and a quantum convolutional layer; during local training, firstly, classic features are extracted by a classic convolutional layer, and then the classic features are coded and input into a quantum convolutional layer to generate quantum features; and the two features are spliced and then classified, and model parameters are uploaded. And the server side adopts a FedAvg algorithm to aggregate parameters so as to update the global model. According to the method, a transfer learning mechanism is introduced to optimize the initialization of the quantum layer, and an experimental result shows that the classification performance and robustness of the method are remarkably superior to those of a traditional federated CNN model on a non-IID image data set, and the method is particularly suitable for a privacy protection cooperative computing scene.