Digital resource full life cycle management method and device based on block chain

Abstract

The invention discloses a digital resource full life cycle management method and device based on a block chain, and relates to the technical field of information security and block chains, and the method comprises the steps: building a quantum communication link between users, and generating a shared quantum key through quantum key distribution (QKD); the sending user encrypts the digital resources owned by the sending user by using the quantum key, and records the encrypted digital resources on the block chain; the sending user sends the encrypted digital resource to other users through a secure channel, and after the other users receive the encrypted digital resource, the shared quantum key is used for decrypting the digital resource on the block chain, and the integrity of the digital resource is verified; historical digital resource data about digital resource access are collected, a machine learning algorithm is applied based on historical data to construct an intelligent contract model, the historical digital resource data are input into the intelligent contract model for training, and meanwhile a dynamic strategy value is output; and adjusting parameters of the intelligent contract model according to the feedback information.

Description

Technical Field

[0001] The present invention relates to the field of information security and blockchain technology, and in particular to a blockchain-based digital resource full life cycle management method and device. Background Art

[0002] With the rapid development of information technology, the secure management and efficient utilization of digital resources has become an increasingly important research field. Traditional digital resource management methods mainly rely on centralized database systems to ensure data security and privacy through access control lists (ACLs) or role-based access control (RBAC) mechanisms. However, with the application of emerging technologies such as cloud computing, big data, and the Internet of Things, traditional methods have gradually exposed their limitations, especially in terms of data transmission security and integrity verification. Existing technologies often cannot provide sufficient protection. In addition, the dynamic management of digital resources also faces challenges. For example, how to optimize resource allocation strategies based on user behavior patterns and historical data has become a problem to be solved. In recent years, blockchain technology has gradually been applied to digital resource management due to its decentralization, immutability, and transparency, providing new solutions. However, there are still many challenges in the actual application of blockchain technology, such as slow transaction processing speed and limited smart contract functions.

[0003] Although the existing blockchain technology has been able to enhance the security and traceability of digital resources to a certain extent, it still has shortcomings in encrypted communication and dynamic resource allocation. First, during the data transmission process, although traditional encryption algorithms can provide a certain degree of security, their security still needs to be improved in the face of high-level network attacks. Secondly, the existing smart contract models usually lack flexibility and cannot dynamically adjust resource allocation strategies based on real-time feedback information. Especially when dealing with large-scale data sets, how to effectively use historical data for predictive analysis and generate optimal strategies is still a difficult problem. In addition, the existing digital resource management system often seems to be unable to cope with complex and changeable user needs, resulting in poor user experience. Therefore, developing a method that can both ensure data transmission security and realize intelligent resource management is of great significance to improving the overall management level of digital resources. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a blockchain-based digital resource full life cycle management method to solve the problem that although traditional encryption algorithms can provide certain security guarantees during data transmission, their security still needs to be improved when facing high-level network attacks.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides a digital resource full life cycle management method based on blockchain, which comprises: Establish a quantum communication link between users and use quantum key distribution (QKD) to generate a shared quantum key. The sending user uses the quantum key to encrypt the digital resources it owns and records the encrypted digital resources on the blockchain; The sending user sends the encrypted digital resources to other users through a secure channel. After receiving the digital resources, other users use the shared quantum key to decrypt the digital resources on the blockchain and verify their integrity. Collect historical digital resource data about digital resource access, apply machine learning algorithms based on historical data to build smart contract models, input historical digital resource data into smart contract models for training, and output dynamic policy values; Deploy the trained smart contract to the blockchain environment, monitor the running status in real time, and adjust the parameters of the smart contract model based on the feedback information.

[0007] As a preferred solution of the blockchain-based digital resource full life cycle management method of the present invention, wherein: the quantum communication link is established between users, and the shared quantum key is generated using quantum key distribution QKD, and the specific steps are: Establishing a quantum communication link between users by sending quantum state photons using a quantum key distributor; Use BB84 protocol for quantum key generation and distribution; Send the user to select a set of polarization angles and the corresponding measurement basis ,in, Indicates For each quantum state photon, the sending user sets the quantum state according to the polarization state of the single quantum state photon and sends the quantum state photon to other users through the optical fiber; The sending user selects a measurement basis through a quantum key distributor, and prepares the polarization state of the quantum state photon according to the selected measurement basis; After receiving the quantum state photons, other users randomly select a measurement basis to perform measurement; When other users choose the same measurement basis as the sending user to perform measurement, the initial polarization state of the quantum state photon is determined; otherwise, the measurement result is random; After completing the sending and receiving of quantum state photons, the sending user and other users publicly disclose their measurement basis choices. When both parties choose the same measurement basis, the corresponding measurement results are retained as a shared quantum key.

[0008] As a preferred solution of the blockchain-based digital resource full life cycle management method of the present invention, the sending user uses a quantum key to encrypt the digital resources it owns, and records the encrypted digital resources on the blockchain. The specific steps are: The digital resources refer to document data, image data, audio data and video data; The sending user uses the shared quantum key generated in the quantum key distribution process as the AES-256 key to encrypt the digital resources owned by the sending user. Each type of digital resource is encrypted according to the same process; Set the encrypted digital resource collection to , Indicates An encrypted digital resource, Indicates belonging to; After the encryption process is completed, the sending user generates corresponding metadata for each encrypted digital resource, expressed as: ; in, Indicates The metadata generated by the encrypted digital resource, Indicates The resource ID generated by the encrypted digital resource, Indicates The ownership information generated by the encrypted digital resource, Indicates The timestamp generated by the encrypted digital resource; Use blockchain technology Ethereum to record encrypted digital resources and their metadata.

[0009] As a preferred solution of the blockchain-based digital resource full life cycle management method of the present invention, the sending user sends the encrypted digital resource to other users through a secure channel. After receiving the digital resource, the other users use the shared quantum key to decrypt the digital resource on the blockchain and verify its integrity. The specific steps are as follows: A secure channel is established between the sending user and other users through the TLS protocol; The sending user sends the encrypted digital resources and their metadata to other users through the TLS secure channel; Other users receive encrypted digital resources and metadata Finally, the shared quantum key generated by QKD is used as the key of AES-256 for decryption; Set the hash value of the original digital resource to ; Use the SHA-256 hash algorithm to calculate the hash value of the decrypted digital resource , and compare it with the hash value provided by the sending user; Other users will use the hash value of the original digital resource and the hash value of the decrypted digital resource Compare them. When the two are equal, it means the data is complete and has not been tampered with; otherwise, the data is damaged or tampered with.

[0010] As a preferred solution of the blockchain-based digital resource life cycle management method of the present invention, the historical digital resource data on digital resource access is collected, and a smart contract model is constructed based on the historical data using a machine learning algorithm, specifically: After completing the encryption, transmission and decryption verification of digital resources, obtain the historical digital resource data from the blockchain log and extract the key feature vector from the historical digital resource data. ; Choose to use the long short-term memory network LSTM as the machine learning algorithm to build the smart contract model; The key feature vector As input, the input layer of the smart contract model receives the key feature vector , multiple hidden layers are used to capture the temporal dependencies in the key feature vectors, and the output layer produces a dynamic policy value.

[0011] As a preferred solution of the blockchain-based digital resource life cycle management method of the present invention, the input of historical digital resource data into the smart contract model for training and the output of dynamic strategy values ​​at the same time refer to the key feature vector Enter the smart contract model, the expression is: ; ; ; ; ; ; ; in, represents the output of the input gate, and are the weight matrix and bias term of the input gate respectively, represents the output of the forget gate, and are the weight matrix and bias term of the forget gate respectively, Indicates at time The hidden state of represents the activation function Sigmoid, represents the output of the output gate, and are the weight matrix and bias term of the output gate respectively, Indicates at time The memory state of the LSTM unit is Indicates at time The memory state of the LSTM unit is and are the weight matrix and bias term of the memory state respectively, Indicates at time The hidden state of represents the hyperbolic tangent function, and Indicates at time The weight matrix and bias term of the policy value, Indicates at time The dynamic policy value of represents the weight coefficient of the real-time strategy, Indicates at time The strategy value of represents the attenuation rate, represents the integral variable, Represents each time point in the integration interval The strategy value on A baseline value that represents a minimum resource allocation.

[0012] As a preferred solution of the blockchain-based digital resource life cycle management method of the present invention, the trained smart contract model is deployed in the blockchain environment, the running status is monitored in real time, and the parameters of the smart contract model are adjusted according to the feedback information. The specific steps are as follows: Set the user's access frequency and user satisfaction score as feedback information, and continuously collect the user's access frequency and user satisfaction score. The user satisfaction score is obtained by filling out the questionnaire; The dynamic adjustment amount is calculated based on the feedback information, and the expression is: ; in, Indicates at time The parameter adjustment amount, represents the number of samples, An index variable representing time, Indicates The actual satisfaction rating at that time, Indicates The target satisfaction score at that time, represents the adjustment coefficient, represents the base of natural logarithms, represents the forgetting factor, Indicates at time The frequency of visits, represents the integral variable; according to Update the parameters of the smart contract model, the expression is: ; in, Indicates at time No. parameters, Indicates The learning rate of the parameters.

[0013] In the second aspect, the present invention provides a digital resource full life cycle management device based on blockchain, including a quantum key distribution module, a digital resource encryption module, a digital resource decryption module, a smart contract model construction module and a dynamic adjustment module: The quantum key distribution module is responsible for establishing a quantum communication link between users and generating a shared quantum key through quantum key distribution (QKD) technology. It uses the BB84 protocol to ensure the security of the key and prevent eavesdropping. The digital resource encryption module is used to use the quantum key to perform AES-256 encryption processing on the digital resources owned by the user, and record the encrypted digital resources and their metadata on the blockchain; The digital resource decryption module is responsible for decrypting the encrypted digital resource using the shared quantum key once it is sent to other users through a secure channel, and verifying the integrity of the decrypted data using the SHA-256 hash algorithm; The smart contract model building module is responsible for extracting historical data about digital resource access from blockchain logs and applying machine learning algorithms to build a smart contract model; The dynamic adjustment module is used to continuously collect users' access frequencies and satisfaction scores as feedback information, calculate dynamic adjustment amounts, and update the parameters of the smart contract model accordingly.

[0014] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the blockchain-based digital resource life cycle management method as described in the first aspect of the present invention.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the blockchain-based digital resource life cycle management method as described in the first aspect of the present invention.

[0016] The beneficial effects of the present invention are as follows: the present invention realizes a highly secure data transmission channel by establishing a quantum communication link and using quantum key distribution QKD to generate a shared key, effectively preventing eavesdropping and data leakage, using quantum keys to perform AES-256 encryption on digital resources, and recording the encrypted resources on the blockchain, thereby ensuring the confidentiality and non-tamperability of the data and enhancing the overall security and reliability, transmitting encrypted data through a secure channel of the TLS protocol, and using SHA-256 to verify data integrity, thereby ensuring the security and consistency of the data transmission process, collecting historical data on digital resource access, and applying the LSTM machine learning algorithm to build a smart contract model, thereby realizing the optimization of dynamic resource allocation strategies and improving service efficiency and user experience, and finally, by real-time monitoring of the running status of the smart contract and adjusting parameters according to feedback information, self-optimization and continuous improvement are realized, and the response speed and flexibility are improved. These measures jointly ensure the efficient, secure management and optimized configuration of digital resources throughout their life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 This is a flowchart of the blockchain-based digital resource full life cycle management method in Example 1.

[0019] Figure 2 This is a schematic diagram of the blockchain-based digital resource full life cycle management device in Example 1. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and provides a digital resource full life cycle management method based on blockchain, comprising the following steps: S1. A quantum communication link is established between users, and a pair of shared quantum keys are generated using quantum key distribution (QKD). Establishing a quantum communication link between users by sending quantum state photons using a quantum key distributor; The BB84 protocol is used for quantum key generation and distribution. The BB84 protocol is one of the classic protocols in quantum key distribution. It uses the basic characteristics of quantum mechanics, such as the no-cloning theorem and the Heisenberg uncertainty principle, to ensure the security of the key. It does not rely on a specific hardware system and can be implemented by simply following the protocol. It is applicable to a wide range of scenarios. The user prepares a quantum key distribution device (QKD device), which can generate and detect the quantum state of a single photon. The device needs to have the ability to adjust the polarization angle so that it can select the appropriate basis for the preparation and measurement of the quantum state according to the BB84 protocol; Send the user to select a set of polarization angles and the corresponding measurement basis ,in, Indicates For each quantum state photon, the sending user sets the quantum state according to the polarization state of the single quantum state photon and sends the photon of the quantum state to other users through the optical fiber; The quantum state represents the polarization state of a single quantum state photon, and the measurement basis includes the right angle basis and the diagonal basis; Orthogonal basis: includes horizontal polarization and vertical polarization. If the sender chooses this basis to prepare photons, the receiver must also use the same basis to measure in order to accurately identify the polarization direction. Diagonal basis: includes +45 degree polarization and -45 degree polarization. Similarly, the polarization information of the photon can only be correctly decoded when the sender and receiver use the same type of basis. The sending user randomly selects a measurement basis (rectangular basis or diagonal basis) through the quantum key distributor, and then prepares the polarization state of the photon according to the selected measurement basis; After receiving quantum state photons, other users will also randomly select a measurement basis to perform measurements; When other users choose the same measurement basis as the sending user to perform measurements, the initial polarization state of the quantum state photon can be determined; otherwise, the measurement result is random; After completing the sending and receiving of quantum state photons, the sending user and other users publicly disclose their measurement basis choices (but do not disclose the specific measurement results). Only when both parties choose the same measurement basis will the corresponding measurement results be retained as a shared quantum key. In this way, the sending user and other users can obtain a shared quantum key, which is generated by exchanging and comparing quantum states, and due to the basic properties of quantum mechanics, any eavesdropping will be detected.

[0024] S2. The sending user uses the quantum key to encrypt the digital resources it owns and records the encrypted digital resources on the blockchain; Digital resources refer to document data, image data, audio data, and video data; The sending user uses the shared quantum key generated in the quantum key distribution process as the AES-256 key to encrypt the digital resources owned by the sending user. Each type of digital resource is encrypted according to the same process; Set the encrypted digital resource collection to , Indicates An encrypted digital resource, Indicates belonging to; High-intensity data security is achieved by using quantum keys to encrypt digital resources owned by the sending user using AES-256. AES-256 is a widely used symmetric encryption standard that is selected for its high-intensity security and relatively fast computing speed. This step not only ensures confidentiality during data transmission, but also prevents unauthorized access. Especially when it comes to highly sensitive data, such as financial transaction records or personal privacy information, AES-256 encryption can significantly improve data security and reduce the risk of leakage. After the encryption process is completed, the sending user generates corresponding metadata for each encrypted digital resource, expressed as: ; in, Indicates The metadata generated by the encrypted digital resource, Indicates The resource ID generated by the encrypted digital resource is implemented using the UUID generation algorithm. Indicates The ownership information generated by the encrypted digital resource, Indicates The timestamp generated by the encrypted digital resource; After the encryption process is completed, the sending user generates corresponding metadata for each encrypted digital resource and records it on the blockchain. This process not only enhances the traceability and transparency of the data, but also simplifies the management and audit process. For example, during the internal audit process, metadata provides detailed information support so that each record can be accurately tracked and verified. In addition, the resource ID is generated using the UUID generation algorithm to ensure the uniqueness of each resource and avoid duplicate records or confusion. Metadata refers to resource ID, ownership information, and timestamp. AES-256 is selected as the encryption algorithm. AES-256 is a widely used symmetric encryption standard that is selected for its high security and relatively fast operation speed. Ownership attribution information refers to user names and organization names; Use blockchain technology Ethereum to record encrypted digital resources and their metadata. Ethereum is an open source blockchain platform that supports smart contract functions and is very suitable for implementing complex business logic and data management needs; Using Ethereum to record encrypted digital resources and their metadata further improves security and reliability. As an open source blockchain platform, Ethereum supports smart contract functions and is very suitable for implementing complex business logic and data management needs. The immutability and decentralization of blockchain technology ensure the consistency and integrity of data and prevent malicious tampering, which is particularly important for application scenarios that require a high degree of trust and transparency, such as supply chain management and intellectual property protection.

[0025] S3. The sending user sends the encrypted digital resources to other users through a secure channel. After receiving the digital resources, other users use the shared quantum key to decrypt the digital resources on the blockchain and verify their integrity. The sending user has generated a pair of shared quantum keys using quantum key distribution (QKD), and used the key as the AES-256 key to encrypt the digital resources it owns; The sending user also generates metadata for each encrypted digital resource and records it on the Ethereum blockchain; A secure channel is established between the sending user and other users through the TLS protocol. The TLS protocol provides end-to-end encrypted communication to ensure that data will not be eavesdropped or tampered with during transmission; The sending user sends the encrypted digital resource and its metadata to other users through the TLS secure channel. The encrypted digital resource is set to C and the metadata is set to ; Other users receive the encrypted digital resource C and metadata Finally, the shared quantum key generated by QKD is used as the key of AES-256 for decryption. The expression is: ; in, Indicates the use of AES-256 decryption function Decrypt C, decryption function Refers to the process of decryption using the AES-256 (Advanced Encryption Standard, 256-bit key length) symmetric encryption algorithm. Represents the decrypted digital resource. represents the shared quantum key generated by QKD; Set the hash value of the original digital resource to ; Use the SHA-256 hash algorithm to calculate the hash value of the decrypted digital resource , and compare it with the hash value provided by the sending user to verify whether the decrypted digital resource is complete and has not been tampered with. The expression is: ; in, Indicates the hash value of the decrypted data received. Indicates that the hash value of the decrypted data is calculated using the SHA-256 hash function; Other users will use the hash value of the original digital resource and the hash value of the decrypted digital resource Compare them. When the two are equal, it means the data is complete and has not been tampered with; otherwise, the data is damaged or tampered with.

[0026] S4. Collect historical digital resource data about digital resource access, apply machine learning algorithms based on the historical data to build a smart contract model, input the historical digital resource data into the smart contract model for training, and output dynamic policy values; After completing the encryption, transmission and decryption verification of digital resources, obtain the historical digital resource data from the blockchain log and extract the key feature vector from the historical digital resource data. , the expression is: ; in, Indicates time, Indicates at time User ID, Indicates at time The resource type, Indicates at time The access time, Indicates at time Frequency of visits; Resource types refer to four resource types: document data, image data, audio data, and video data; We choose to use the long short-term memory network LSTM as the machine learning algorithm to build the smart contract model. LSTM is a special recurrent neural network RNN ​​that is very suitable for processing and predicting time series data. As input, the input layer of the smart contract model receives the key feature vector , through multiple hidden layers to capture the time dependency in the key feature vector, the output layer produces a dynamic policy value to guide subsequent resource allocation decisions; Inputting historical digital resource data into the smart contract model for training and outputting dynamic strategy values ​​at the same time means converting the key feature vector Enter the smart contract model, the expression is: ; ; ; ; ; ; ; in, represents the output of the input gate, and are the weight matrix and bias term of the input gate respectively, represents the output of the forget gate, and are the weight matrix and bias term of the forget gate respectively, Indicates at time The hidden state of represents the activation function Sigmoid, represents the output of the output gate, and are the weight matrix and bias term of the output gate respectively, Indicates at time The memory state of the LSTM unit is Indicates at time The memory state of the LSTM unit is and are the weight matrix and bias term of the memory state respectively, Indicates at time The hidden state of represents the hyperbolic tangent function, and Indicates at time The weight matrix and bias term of the policy value, Indicates at time The dynamic policy value of represents the weight coefficient of the real-time strategy, Indicates at time The strategy value of represents the attenuation rate, represents the integral variable, Represents each time point in the integration interval The strategy value on Is a variable used to describe the time from time 0 to the current time At all time points within A baseline value representing a minimum resource allocation; By obtaining historical digital resource data from blockchain logs and extracting key feature vectors from them, we can accurately capture user behavior patterns. This time series-based data processing method can effectively reflect the usage of different types of digital resources in different periods of time. For example, in document management scenarios, by analyzing user access time and frequency, peak and trough periods can be identified, thereby optimizing server load distribution, which not only improves response speed but also reduces resource waste.

[0027] S5. Deploy the trained smart contract to the blockchain environment, monitor the running status in real time, and adjust the parameters of the smart contract model based on the feedback information; Set the user's access frequency and user satisfaction score as feedback information, and continuously collect the user's access frequency and user satisfaction score. The user satisfaction score is obtained by filling out the questionnaire; The dynamic adjustment amount is calculated based on the feedback information, and the expression is: ; in, Indicates at time The parameter adjustment amount, represents the number of samples, An index variable representing time, Indicates The actual satisfaction rating at that time, Indicates The target satisfaction score at that time, represents the adjustment coefficient, represents the base of natural logarithms, Represents the forgetting factor, which determines the historical access frequency The degree of influence when calculating the dynamic adjustment amount, Indicates at time The frequency of visits, represents the integral variable; according to Update the parameters of the smart contract model, the expression is: ; in, Indicates at time No. parameters, Indicates The learning rate of the parameters; The dynamic adjustment amount is calculated based on the feedback information. This process comprehensively considers the difference between the actual satisfaction score and the target satisfaction score and the impact of the historical visit frequency. The introduction of the forgetting factor and the adjustment coefficient enables the user to respond quickly to user needs in the short term while maintaining long-term stable performance. According to the calculated dynamic adjustment amount, the parameters of the smart contract model are updated to achieve self-optimization of the smart contract model. The learning rate determines the magnitude of each adjustment. Reasonable settings can accelerate the convergence process and avoid overfitting. For example, in financial trading systems, by dynamically adjusting trading strategy parameters, it is possible to better adapt to market changes and improve transaction success rates. This adaptive adjustment mechanism not only improves flexibility, but also enhances its ability to cope with complex environments.

[0028] This embodiment also provides a digital resource full life cycle management device based on blockchain, including: a quantum key distribution module, a digital resource encryption module, a digital resource decryption module, a smart contract model construction module and a dynamic adjustment module: The quantum key distribution module is responsible for establishing quantum communication links between users and generating shared quantum keys through quantum key distribution (QKD) technology. It uses the BB84 protocol to ensure the security of the key and prevent eavesdropping. Digital resource encryption module, which uses quantum keys to perform AES-256 encryption on digital resources owned by users, and records the encrypted digital resources and their metadata on the blockchain; Digital resource decryption module: Once the encrypted digital resource is sent to other users through a secure channel, this module is responsible for decrypting it using the shared quantum key and verifying the integrity of the decrypted data through the SHA-256 hash algorithm; Smart contract model building module, which is responsible for extracting historical data about digital resource access from blockchain logs and applying machine learning algorithms to build smart contract models; The dynamic adjustment module is used to continuously collect users' access frequency and satisfaction scores as feedback information, calculate the dynamic adjustment amount, and update the parameters of the smart contract model accordingly.

[0029] This embodiment also provides a computer device, which is suitable for the case of a blockchain-based digital resource full life cycle management method, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the blockchain-based digital resource full life cycle management method proposed in the above embodiment.

[0030] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0031] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for implementing the full life cycle management of digital resources based on blockchain as proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0032] In summary, the present invention achieves a highly secure data transmission channel and effectively prevents eavesdropping and data leakage by: establishing a quantum communication link and using quantum key distribution QKD to generate a shared key, using quantum keys to perform AES-256 encryption on digital resources, and recording the encrypted resources on the blockchain, ensuring the confidentiality and non-tamperability of the data and enhancing the overall security and reliability, transmitting encrypted data through a secure channel of the TLS protocol, and using SHA-256 to verify data integrity, ensuring the security and consistency of the data transmission process, collecting historical data on digital resource access, and applying the LSTM machine learning algorithm to build a smart contract model, realizing the optimization of dynamic resource allocation strategies, and improving service efficiency and user experience. Finally, by real-time monitoring of the running status of the smart contract and adjusting parameters based on feedback information, self-optimization and continuous improvement are achieved, and response speed and flexibility are improved. These measures jointly ensure the efficient, secure management and optimized configuration of digital resources throughout their life cycle.

[0033] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A digital resource full life cycle management method based on blockchain, characterized by: include: Establish a quantum communication link between users and use quantum key distribution (QKD) to generate a shared quantum key. The sending user uses the quantum key to encrypt the digital resources it owns and records the encrypted digital resources on the blockchain; The sending user sends the encrypted digital resources to other users through a secure channel. After receiving the digital resources, other users use the shared quantum key to decrypt the digital resources on the blockchain and verify their integrity. Collect historical digital resource data about digital resource access, apply machine learning algorithms based on historical data to build smart contract models, input historical digital resource data into smart contract models for training, and output dynamic policy values; Deploy the trained smart contract to the blockchain environment, monitor the running status in real time, and adjust the parameters of the smart contract model based on the feedback information.

2. The blockchain-based digital resource full life cycle management method according to claim 1, characterized in that: The specific steps of establishing a quantum communication link between users and using quantum key distribution QKD to generate a shared quantum key are as follows: Establishing a quantum communication link between users by sending quantum state photons using a quantum key distributor; Use BB84 protocol for quantum key generation and distribution; Send the user to select a set of polarization angles and the corresponding measurement basis ,in, Indicates For each quantum state photon, the sending user sets the quantum state according to the polarization state of the single quantum state photon and sends the quantum state photon to other users through the optical fiber; The sending user selects a measurement basis through a quantum key distributor, and prepares the polarization state of the quantum state photon according to the selected measurement basis; After receiving the quantum state photons, other users randomly select a measurement basis to perform measurement; When other users choose the same measurement basis as the sending user to perform measurement, the initial polarization state of the quantum state photon is determined; otherwise, the measurement result is random; After completing the sending and receiving of quantum state photons, the sending user and other users publicly disclose their measurement basis choices. When both parties choose the same measurement basis, the corresponding measurement results are retained as a shared quantum key.

3. The blockchain-based digital resource full life cycle management method according to claim 2, characterized in that: The sending user uses the quantum key to encrypt the digital resources it owns, and records the encrypted digital resources on the blockchain. The specific steps are: The digital resources refer to document data, image data, audio data and video data; The sending user uses the shared quantum key generated in the quantum key distribution process as the AES-256 key to encrypt the digital resources owned by the sending user. Each type of digital resource is encrypted according to the same process; Set the encrypted digital resource collection to , Indicates An encrypted digital resource, Indicates belonging to; After the encryption process is completed, the sending user generates corresponding metadata for each encrypted digital resource, expressed as: ； in, Indicates The metadata generated by the encrypted digital resource, Indicates The resource ID generated by the encrypted digital resource, Indicates The ownership information generated by the encrypted digital resource, Indicates The timestamp generated by the encrypted digital resource; Use blockchain technology Ethereum to record encrypted digital resources and their metadata.

4. The blockchain-based digital resource full life cycle management method according to claim 3, characterized in that: The sending user sends the encrypted digital resources to other users through a secure channel. After receiving the digital resources, other users use the shared quantum key to decrypt the digital resources on the blockchain and verify their integrity. The specific steps are as follows: A secure channel is established between the sending user and other users through the TLS protocol; The sending user sends the encrypted digital resources and their metadata to other users through the TLS secure channel; Other users receive encrypted digital resources and metadata Finally, the shared quantum key generated by QKD is used as the key of AES-256 for decryption; Set the hash value of the original digital resource to ; Use the SHA-256 hash algorithm to calculate the hash value of the decrypted digital resource , and compare it with the hash value provided by the sending user; Other users will use the hash value of the original digital resource and the hash value of the decrypted digital resource Compare them. When the two are equal, it means the data is complete and has not been tampered with; otherwise, the data is damaged or tampered with.

5. The blockchain-based digital resource full life cycle management method according to claim 4, characterized in that: The collecting of historical digital resource data on digital resource access and the construction of a smart contract model based on the historical data using a machine learning algorithm are specifically as follows: After completing the encryption, transmission and decryption verification of digital resources, obtain the historical digital resource data from the blockchain log and extract the key feature vector from the historical digital resource data. ; Choose to use the long short-term memory network LSTM as the machine learning algorithm to build the smart contract model; The key feature vector As input, the input layer of the smart contract model receives the key feature vector , multiple hidden layers are used to capture the temporal dependencies in the key feature vectors, and the output layer produces a dynamic policy value.

6. The blockchain-based digital resource full life cycle management method according to claim 5, characterized in that: The input of historical digital resource data into the smart contract model for training and output of dynamic strategy values ​​refers to the input of key feature vectors into the smart contract model for training and output of dynamic strategy values. Enter the smart contract model, the expression is: ； ； ； ； ； ； ； in, represents the output of the input gate, and are the weight matrix and bias term of the input gate respectively, represents the output of the forget gate, and are the weight matrix and bias term of the forget gate respectively, Indicates at time The hidden state of represents the activation function Sigmoid, represents the output of the output gate, and are the weight matrix and bias term of the output gate respectively, Indicates at time The memory state of the LSTM unit is Indicates at time The memory state of the LSTM unit is and are the weight matrix and bias term of the memory state respectively, Indicates at time The hidden state of represents the hyperbolic tangent function, and Indicates at time The weight matrix and bias term of the policy value, Indicates at time The dynamic policy value of represents the weight coefficient of the real-time strategy, Indicates at time The strategy value of represents the attenuation rate, represents the integral variable, Represents each time point in the integration interval The strategy value on A baseline value that represents a minimum resource allocation.

7. The blockchain-based digital resource full life cycle management method according to claim 6, characterized in that: The trained smart contract model is deployed to the blockchain environment, the running status is monitored in real time, and the parameters of the smart contract model are adjusted according to the feedback information. The specific steps are as follows: Set the user's access frequency and user satisfaction score as feedback information, and continuously collect the user's access frequency and user satisfaction score. The user satisfaction score is obtained by filling out the questionnaire; The dynamic adjustment amount is calculated based on the feedback information, and the expression is: ； in, Indicates at time The parameter adjustment amount, represents the number of samples, An index variable representing time, Indicates The actual satisfaction rating at that time, Indicates The target satisfaction score at that time, represents the adjustment coefficient, represents the base of natural logarithms, represents the forgetting factor, Indicates at time The frequency of visits, represents the integral variable; according to Update the parameters of the smart contract model, the expression is: ； in, Indicates at time No. parameters, Indicates The learning rate of the parameters.

8. A digital resource full life cycle management device based on blockchain, based on the digital resource full life cycle management method based on blockchain according to any one of claims 1 to 7, characterized in that: Including quantum key distribution module, digital resource encryption module, digital resource decryption module, smart contract model building module and dynamic adjustment module: The quantum key distribution module is responsible for establishing quantum communication links between users and generating shared quantum keys through quantum key distribution (QKD) technology. It uses the BB84 protocol to ensure the security of the key and prevent eavesdropping. The digital resource encryption module is used to use the quantum key to perform AES-256 encryption processing on the digital resources owned by the user, and record the encrypted digital resources and their metadata on the blockchain; The digital resource decryption module is responsible for decrypting the encrypted digital resource using the shared quantum key once it is sent to other users through a secure channel, and verifying the integrity of the decrypted data using the SHA-256 hash algorithm; The smart contract model building module is responsible for extracting historical data about digital resource access from blockchain logs and applying machine learning algorithms to build a smart contract model; The dynamic adjustment module is used to continuously collect users' access frequencies and satisfaction scores as feedback information, calculate dynamic adjustment amounts, and update the parameters of the smart contract model accordingly.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the blockchain-based digital resource full life cycle management method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the blockchain-based digital resource full life cycle management method described in any one of claims 1 to 7 are implemented.

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