Safety processing method and device for power transaction data and computer equipment

Abstract

The invention relates to a security processing method and device for power transaction data and computer equipment. The method comprises the following steps: in response to a power transaction request, completing a transaction matchmaking operation in a pre-constructed block chain transaction network, and generating power transaction data corresponding to the power transaction request; through a cloud-side-end collaborative architecture, the power transaction data is encrypted and transmitted to a cloud end of the power transaction data security processing platform for storage; in response to a sharing request for the power transaction data, calling the power transaction data from the cloud, and performing desensitization and anonymization processing on the power transaction data to obtain desensitized data of the power transaction data; and executing security evaluation on a receiving end of the sharing request, encrypting the desensitized data under the condition that an evaluation result of the security evaluation is passed, obtaining encrypted desensitized data of the power transaction data, and transmitting the encrypted desensitized data to the receiving end. By adopting the method, the data security of the power transaction data can be improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for secure processing of electricity trading data. Background Technology

[0002] The power trading platform is a core infrastructure in the power market system, enabling the market-based trading of electricity and related services. It provides a transparent and open trading environment for market participants such as power generation companies, electricity retailers, and power users, supporting the buying and selling of electricity products and services, including electricity trading, ancillary service trading, and transmission rights trading. Through end-to-end online services, it enables diversified trading models such as medium- and long-term trading, spot trading, and real-time balancing, covering cross-provincial and intra-provincial trading scenarios. Because power trading data contains sensitive information such as user electricity consumption data, enterprise operating parameters, and market transaction details, its leakage could lead to issues such as the leakage of trade secrets and infringement of user privacy. Therefore, data protection for the power trading platform is particularly important.

[0003] However, existing power trading platforms typically grant permissions by default or static authorization when faced with sharing requests. This approach, with its single sharing path and rigid authorization logic, can easily lead to the leakage of sensitive data during the sharing process, especially in data sharing with multiple parties or external institutions, which poses data security issues. Summary of the Invention

[0004] Therefore, it is necessary to provide a secure processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product for power trading data that can improve the data security of power trading data, in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for securely processing electricity transaction data, including:

[0006] In response to a user's electricity trading request, the system completes the transaction matching operation in a pre-built blockchain trading network and generates electricity trading data corresponding to the electricity trading request.

[0007] Through a cloud-edge-device collaborative architecture, the power trading data is encrypted and transmitted to the cloud of the power trading data security processing platform for storage.

[0008] In response to a request to share the power trading data, the power trading data is retrieved from the cloud, and the power trading data is desensitized and anonymized to obtain desensitized power trading data.

[0009] A security assessment is performed on the receiving end of the sharing request. If the security assessment result is passed, the de-identified data is encrypted to obtain encrypted de-identified data of the power transaction data, and the encrypted de-identified data is transmitted to the receiving end.

[0010] In one embodiment, the step of encrypting and transmitting the power trading data to the cloud of the power trading data security processing platform for storage via a cloud-edge-device collaborative architecture includes:

[0011] When the power trading data is transmitted to the edge node, sensitive information in the power trading data is identified and determined at the edge node.

[0012] The sensitive information in the power trading data is dynamically masked to obtain desensitized power trading data;

[0013] The de-identified power transaction data is encrypted to obtain encrypted data;

[0014] The encrypted data is uploaded to the cloud for storage.

[0015] In one embodiment, the step of encrypting the de-identified data to obtain encrypted de-identified data of the power transaction data, and transmitting the encrypted de-identified data to the receiving end, includes:

[0016] Generate a one-time dynamic key for this data transmission;

[0017] The de-identified data is encrypted using the one-time dynamic key to obtain the encrypted de-identified data of the power transaction data;

[0018] The encrypted and desensitized data and the one-time dynamic key are transmitted to the receiving end through an encrypted channel.

[0019] In one embodiment, the method further includes:

[0020] Dynamically rotate the access key corresponding to the data access party, and monitor the access behavior of the data access party to the power transaction data in real time through the gateway;

[0021] If any abnormal query frequency or abnormal call behavior is detected in the access behavior, the access key corresponding to the data access party will be destroyed.

[0022] In one embodiment, the dynamic rotation operation on the access key corresponding to the data access party includes:

[0023] Based on the security status of the access key, determine the leakage risk level corresponding to the access key;

[0024] Based on the leakage risk level, a corresponding rotation frequency is determined, and the access key is dynamically rotated according to the rotation frequency.

[0025] In one embodiment, determining the leakage risk level corresponding to the access key based on the security status of the access key includes:

[0026] Statistical analysis is performed on the access behavior of the data access party to determine the corresponding behavioral statistics; the behavioral statistics include at least access request frequency, access time distribution, access network address distribution, call failure rate, and access path range;

[0027] Based on the behavioral statistics, the leakage risk level corresponding to the access key is determined.

[0028] Secondly, this application also provides a secure processing device for electricity transaction data, comprising:

[0029] The transaction data generation module is used to respond to the electricity transaction request from the user and complete the transaction matching operation in the pre-built blockchain transaction network to generate electricity transaction data corresponding to the electricity transaction request.

[0030] The transaction data storage module is used to encrypt and transmit the power transaction data to the cloud of the power transaction data security processing platform for storage through a cloud-edge-device collaborative architecture;

[0031] The transaction data anonymization module is used to respond to a sharing request for the electricity transaction data, retrieve the electricity transaction data from the cloud, and perform anonymization and desensitization processing on the electricity transaction data to obtain anonymized data of the electricity transaction data;

[0032] The transaction data sharing module is used to perform a security assessment on the receiving end of the sharing request. If the security assessment result is passed, the de-identified data is encrypted to obtain encrypted de-identified data of the power transaction data, and the encrypted de-identified data is transmitted to the receiving end.

[0033] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0034] In response to a user's electricity trading request, the system completes the transaction matching operation in a pre-built blockchain trading network and generates electricity trading data corresponding to the electricity trading request.

[0035] Through a cloud-edge-device collaborative architecture, the power trading data is encrypted and transmitted to the cloud of the power trading data security processing platform for storage.

[0036] In response to a request to share the power trading data, the power trading data is retrieved from the cloud, and the power trading data is desensitized and anonymized to obtain desensitized power trading data.

[0037] A security assessment is performed on the receiving end of the sharing request. If the security assessment result is passed, the de-identified data is encrypted to obtain encrypted de-identified data of the power transaction data, and the encrypted de-identified data is transmitted to the receiving end.

[0038] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0039] In response to a user's electricity trading request, the system completes the transaction matching operation in a pre-built blockchain trading network and generates electricity trading data corresponding to the electricity trading request.

[0040] Through a cloud-edge-device collaborative architecture, the power trading data is encrypted and transmitted to the cloud of the power trading data security processing platform for storage.

[0041] In response to a request to share the power trading data, the power trading data is retrieved from the cloud, and the power trading data is desensitized and anonymized to obtain desensitized power trading data.

[0042] A security assessment is performed on the receiving end of the sharing request. If the security assessment result is passed, the de-identified data is encrypted to obtain encrypted de-identified data of the power transaction data, and the encrypted de-identified data is transmitted to the receiving end.

[0043] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0044] In response to a user's electricity trading request, the system completes the transaction matching operation in a pre-built blockchain trading network and generates electricity trading data corresponding to the electricity trading request.

[0045] Through a cloud-edge-device collaborative architecture, the power trading data is encrypted and transmitted to the cloud of the power trading data security processing platform for storage.

[0046] In response to a request to share the power trading data, the power trading data is retrieved from the cloud, and the power trading data is desensitized and anonymized to obtain desensitized power trading data.

[0047] A security assessment is performed on the receiving end of the sharing request. If the security assessment result is passed, the de-identified data is encrypted to obtain encrypted de-identified data of the power transaction data, and the encrypted de-identified data is transmitted to the receiving end.

[0048] The aforementioned secure processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product for electricity trading data first responds to electricity trading requests from users and completes transaction matching operations within a pre-built blockchain trading network, generating electricity trading data corresponding to the electricity trading request. Blockchain technology, with its immutable and traceable characteristics, ensures the technical credibility of the electricity trading data generation process, effectively preventing the platform or trading parties from tampering with the trading process or results, thus enhancing the integrity and credibility of the trading data. Then, through a cloud-edge-device collaborative architecture, the electricity trading data is encrypted and transmitted to the cloud of the electricity trading data secure processing platform for storage. Combined with a multi-layered architecture and transmission encryption technology, this effectively reduces the risk of data interception, theft, or tampering during transmission, ensuring the confidentiality and integrity of the data during transmission and enhancing the platform's capabilities. The system provides robust data protection capabilities. Next, in response to requests to share electricity trading data, it retrieves the data from the cloud and performs anonymization and desensitization processing to obtain desensitized electricity trading data. This prevents data recipients from reconstructing the original user identity or company information through reverse reasoning or cross-referencing, effectively reducing the risk of sensitive information leakage and achieving sharing compliance without affecting the value of data analysis. Finally, a security assessment is performed on the receiving end of the sharing request. If the security assessment passes, the desensitized data is encrypted to obtain encrypted desensitized electricity trading data, which is then transmitted to the receiving end. A dynamic security assessment mechanism is introduced before the data is officially shared, dynamically blocking high-risk recipients from accessing the data. This enhances the platform's control over the sharing process, while encryption ensures data security throughout the sharing process. The aforementioned method utilizes a blockchain network to complete power transaction matching operations, ensuring the immutability and traceability of transaction data generation. The encrypted transmission mechanism based on a cloud-edge-device architecture effectively enhances data security during transmission. When responding to sharing requests, de-identification and anonymization processes are introduced to reduce the risk of sensitive fields being exposed. Furthermore, by conducting security assessments of data recipients, encrypted and de-identified data is generated and shared only after the assessment is passed, effectively preventing unauthorized access to sensitive information. Overall, the solution improves the security, flexibility, and compliance of the power trading platform in multi-party collaboration and data sharing scenarios. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart illustrating a method for securely processing electricity transaction data in one embodiment;

[0051] Figure 2 This is a flowchart illustrating the dynamic management steps of access keys in one embodiment;

[0052] Figure 3 This is a schematic diagram of a privacy protection and data encryption system for an electricity trading platform in one embodiment;

[0053] Figure 4 This is a flowchart illustrating the process of implementing the privacy protection and data encryption method of the power trading platform in one embodiment.

[0054] Figure 5 This is a structural block diagram of a power transaction data security processing device in one embodiment;

[0055] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0057] In one embodiment, such as Figure 1 As shown, a secure processing method for electricity trading data is provided. This embodiment illustrates the method by applying it to a server, specifically an electricity trading data secure processing platform running on the server. It is understood that this method can also be applied to terminals, or to systems including terminals and servers, and is implemented through interaction between the terminal and the server. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, and tablets. In this embodiment, the method includes the following steps:

[0058] Step S101: In response to the electricity trading request from the user, the transaction matching operation is completed in the pre-built blockchain trading network, and electricity trading data corresponding to the electricity trading request is generated.

[0059] Among them, an electricity trading request refers to the instruction information containing the trading intent submitted by electricity market participants (including power generation companies, electricity sales companies, electricity users, etc.) through a client. The trading intent includes, but is not limited to, the trading type, target electricity volume, expected electricity price, time period, etc.; the blockchain trading network refers to the chain-like matching system of the electricity market composed of multiple nodes. This network uses smart contracts to record matching behavior to ensure that the trading process is open, tamper-proof, and traceable.

[0060] For example, after receiving an electricity trading request from a power generation company or electricity sales company, the server first formats the request data and writes it into the trading pool of the blockchain trading network. Then, the matching mechanism within the blockchain network executes the matching operation according to rules such as supply and demand and price matching. After the matching is completed, the server structures the successfully matched transaction results into electricity trading data. This data includes fields such as the traded electricity volume, traded electricity price, transaction time, and identifiers of both parties, and serves as the basic data unit for subsequent transmission, storage, and sharing.

[0061] Step S102: Through the cloud-edge-device collaborative architecture, the power trading data is encrypted and transmitted to the cloud of the power trading data security processing platform for storage.

[0062] Among them, the cloud-edge-device collaborative architecture refers to a layered data processing architecture composed of terminal devices, edge nodes and cloud platforms. The terminal is used to collect and submit power trading data, the edge node is used for local processing and de-identification engine deployment, and the cloud platform is used for data center management and secure storage.

[0063] Encrypted transmission refers to the use of multi-layered security mechanisms in the data transmission link.

[0064] For example, the server first pushes electricity transaction data to an edge node close to the data source. At the edge node, a locally deployed de-identification engine dynamically masks sensitive information, including user identity and geographic location fields (e.g., retaining the first three characters and replacing subsequent characters with mask symbols), generating preliminary de-identified data. Subsequently, this data is uploaded to the cloud platform via a TLS (Transport Layer Security) encrypted channel through the edge node, where it is centrally stored and managed. Throughout the entire transmission path, the data remains encrypted, effectively preventing information leakage and unauthorized interception during transmission.

[0065] Step S103: In response to the request to share electricity trading data, the electricity trading data is retrieved from the cloud and then desensitized and anonymized to obtain desensitized electricity trading data.

[0066] In this context, a data sharing request refers to a request instruction initiated by an entity with data access needs (such as regulatory agencies, market analysts, or other authorized electricity market participants). The request content may include the scope of the shared data, field types, and a declaration of its intended use. De-identification and anonymization processes refer to the de-identification, perturbation, and quasi-identifier obfuscation of information involving sensitive fields in electricity transaction data. These fields include, but are not limited to, user identifiers, geographical locations, and transaction amounts. The aim is to reduce the risk of reverse engineering of the data without affecting its overall structure and analytical value.

[0067] For example, after retrieving the electricity transaction data to be shared from cloud storage, the server performs multi-layered processing based on a preset anonymization strategy. This includes replacing user identification information with hash values; overlaying Gaussian-distributed noise perturbations onto numerical fields (such as transaction amounts) to obscure the true value while maintaining statistical trends; and performing K-anonymization on combinations of fields with strong identification capabilities (such as geographic location + user type + time interval) to ensure that each record has at least k duplicate records in the quasi-identifier space, thereby blocking the tracing path. Through this combined processing, the server generates a data copy that can be used for controlled sharing, i.e., anonymized electricity transaction data.

[0068] Step S104: Perform a security assessment on the receiving end of the sharing request. If the security assessment result is passed, encrypt the de-identified data to obtain encrypted de-identified data of the power transaction data, and transmit the encrypted de-identified data to the receiving end.

[0069] The receiving end refers to the data access entity that initiates the sharing request, including market participants or regulatory bodies with compliant access authorization; the security assessment is an evaluation process that comprehensively judges the identity attributes, access history, risk level, and other information of the receiving end, and the assessment results are used to dynamically determine whether to allow it to access the corresponding data content.

[0070] For example, upon receiving a sharing request, the server retrieves the recipient's user information and data from the platform's credit system, combining these with factors such as access frequency, historical call behavior, and the current session environment to construct a security scoring model and perform real-time risk analysis on the recipient. If the evaluation result meets a preset security threshold, the server performs a one-time encryption operation on the processed de-identified data, for example, using a symmetric encryption algorithm such as AES (Advanced Encryption Standard), combined with a temporary key generated by the platform's key generation module, to complete the encryption and form encrypted de-identified data. Subsequently, the server transmits this encrypted de-identified data to the recipient through an encrypted communication channel, and sets a key expiration mechanism after transmission to ensure that the data can only be accessed and decrypted within a limited time and authorized scope.

[0071] In the aforementioned secure processing method for electricity trading data, firstly, in response to electricity trading requests from users, a transaction matching operation is completed in a pre-built blockchain trading network, generating electricity trading data corresponding to the electricity trading request. Blockchain technology possesses the characteristics of immutability and traceability, ensuring the technical credibility of the electricity trading data generation process and effectively preventing the platform or trading parties from tampering with the trading process or results, thus enhancing the integrity and credibility of the trading data. Then, through a cloud-edge-device collaborative architecture, the electricity trading data is encrypted and transmitted to the cloud of the electricity trading data secure processing platform for storage. Combined with a multi-layered architecture and transmission encryption technology, the risk of data interception, theft, or tampering during transmission is effectively reduced, ensuring the confidentiality and integrity of the data during transmission and improving the platform's data protection capabilities. Next, in response to... For requests to share electricity trading data, the system retrieves the data from the cloud and performs anonymization and desensitization processing to obtain desensitized electricity trading data. This prevents the data recipient from reconstructing the original user identity or enterprise information through reverse reasoning or cross-referencing, effectively reducing the risk of sensitive information leakage and achieving compliance in data sharing without affecting the value of data analysis. Finally, a security assessment is performed on the receiving end of the sharing request. If the security assessment result is satisfactory, the desensitized data is encrypted to obtain encrypted desensitized electricity trading data, which is then transmitted to the receiving end. A dynamic security assessment mechanism is introduced before the data is officially shared, which can dynamically block high-risk recipients from accessing the data, enhancing the platform's control over the sharing process. At the same time, encryption ensures the security of the data in the sharing chain. The aforementioned method utilizes a blockchain network to complete power transaction matching operations, ensuring the immutability and traceability of transaction data generation. The encrypted transmission mechanism based on a cloud-edge-device architecture effectively enhances data security during transmission. When responding to sharing requests, de-identification and anonymization processes are introduced to reduce the risk of sensitive fields being exposed. Furthermore, by conducting security assessments of data recipients, encrypted and de-identified data is generated and shared only after the assessment is passed, effectively preventing unauthorized access to sensitive information. Overall, the solution improves the security, flexibility, and compliance of the power trading platform in multi-party collaboration and data sharing scenarios.

[0072] In an exemplary embodiment, step S102 above, through a cloud-edge-device collaborative architecture, encrypts and transmits power trading data to the cloud of the power trading data security processing platform for storage. It further includes: when the power trading data is transmitted to an edge node, identifying sensitive information in the power trading data at the edge node; performing dynamic data masking on the sensitive information in the power trading data to obtain desensitized power trading data; performing encryption processing on the desensitized power trading data to obtain encrypted data; and uploading the encrypted data to the cloud for storage.

[0073] Sensitive information refers to fields in electricity transaction data that may lead to the leakage of user identity, exposure of geographical location, or leakage of enterprise operation data. These fields include, but are not limited to, user identification information, electricity address, equipment number, and transaction time.

[0074] For example, after the server completes the initial generation of power transaction data, it sends the data to the corresponding edge node according to the system configuration. The data processing module running on the edge node first loads the desensitization rule template library and performs field parsing on the received data to extract content that is predefined as sensitive fields, including user identifier field, geographic location field, and device ID field.

[0075] Subsequently, the server-controlled desensitization engine executes corresponding dynamic masking strategies based on the field type: for the user identifier field, a character position mask is used, retaining only the first 3 characters and replacing the rest with asterisks "*"; for the geographic location field, provincial and municipal administrative division information is extracted and retained, while detailed street information is truncated; for the device ID field, format scrambling and random suffix replacement are performed to prevent the device's uniqueness from being exposed. All of the above processing is performed locally on the edge node, ensuring that the original sensitive information does not leave the edge.

[0076] After the data anonymization process is complete, the server schedules the encryption service component within the edge nodes to encapsulate the anonymized data into a standardized structure and then uses the AES (Advanced Encryption Standard) algorithm in conjunction with the current session key to encrypt the structure. The key is uniformly distributed by the platform's key management module and supports periodic rotation. After encryption, the server uploads the encrypted data to the cloud data processing platform through an established TLS (Transport Layer Security) encrypted tunnel. The cloud platform then stores the data and records upload logs and unique identifiers for subsequent retrieval, verification, and sharing.

[0077] In this embodiment, by introducing a cloud-edge-device collaborative architecture during power transaction data transmission, and performing sensitive information identification, dynamic masking, and encryption processing at the edge nodes, not only is the risk of original sensitive data being exposed during transmission effectively prevented, but a local privacy protection strategy of "data not leaving the source" is also achieved. Compared to centralizing desensitization and encryption in the cloud, this embodiment offers superior data control granularity and stronger anti-leakage capabilities, reducing the security risks of data being eavesdropped on, intercepted, or reconstructed during transmission. Furthermore, by combining a unified encryption mechanism and secure channel, this embodiment achieves structured desensitization and encrypted encapsulation of power transaction data before it is uploaded to the cloud, significantly improving the security and compliance of data throughout the entire process from the edge to the cloud.

[0078] In an exemplary embodiment, step S104 above, which encrypts the de-identified data to obtain encrypted de-identified data of power transaction data, and transmits the encrypted de-identified data to the receiving end, further includes: generating a one-time dynamic key for this data transmission; using the one-time dynamic key to encrypt the de-identified data to obtain encrypted de-identified data of power transaction data; and transmitting the encrypted de-identified data and the one-time dynamic key to the receiving end respectively through an encrypted channel.

[0079] Among them, a one-time dynamic key refers to a symmetric encryption key that is temporarily generated in the current data sharing task and is only used for this transmission and decryption. This key has the characteristics of being used only once and automatically expiring after access, and is used to improve transmission security and prevent data reuse. An encrypted channel refers to a two-way encrypted data channel established using methods such as TLS (Transport Layer Security) or VPN (Virtual Private Network) to ensure the confidentiality and anti-interception capability of the key and encrypted data during transmission.

[0080] For example, after receiving a request for de-identified data sharing initiated by an electricity market entity and completing the security assessment process for the receiving end, the server first calls the platform's Key Management Module to dynamically generate a one-time symmetric key. This key has an identification tag associated with a unique request number and is registered as "valid" in the key lifecycle database. At the same time, the access count is initialized to "1".

[0081] Subsequently, the server binds the one-time key to the current task and invokes the local encryption service component to encapsulate the anonymized data obtained in the previous step into a standard data structure, including metadata such as field tags, timestamps, and data source identifiers. During the encryption process, the server uses the AES (Advanced Encryption Standard) algorithm, specifying the one-time key as the encryption key, to encrypt the complete structure, generating encrypted and anonymized power transaction data. This key can only be successfully decrypted once at the receiving end; it will automatically expire after exceeding the number of uses or the set validity period (e.g., 30 minutes).

[0082] To further enhance security, the server establishes two encrypted channels: one sends encrypted and de-identified data to the receiving end via a TLS (Transport Layer Security) secure channel, and the other encrypts and encapsulates a one-time key via a platform-controlled key service channel and sends it independently. Upon receiving both channels, the receiving end uses the key in its local decryption environment to decrypt the data. After successful decryption, the server receives a key usage receipt, immediately marks the key as "expired," and records the key status change log and sharing completion event to the platform's audit module.

[0083] In this embodiment, by introducing a one-time dynamic key mechanism, temporary key encryption and automatic expiration control are implemented during the sharing of de-identified data. Combined with dual-channel encrypted transmission, this ensures that encrypted data and decryption keys are transmitted separately, significantly reducing the risk of data leakage during transmission. This effectively solves the problems of key reuse and data decryption in traditional sharing methods, improving the platform's granularity of access control and security of transmission paths for sensitive de-identified data.

[0084] In one exemplary embodiment, such as Figure 2 As shown, the above-mentioned method for securely processing electricity transaction data also includes the following steps:

[0085] Step S201: Perform a dynamic rotation operation on the access key corresponding to the data access party, and monitor the access behavior of the data access party to the power transaction data in real time through the gateway.

[0086] Step S202: If abnormal query frequency or abnormal call behavior is detected in the access behavior, the access key corresponding to the data access party is destroyed.

[0087] Among them, the data access party refers to the entity requesting access to electricity trading data, including but not limited to electricity market participants, external regulatory agencies, or data analysis service providers; the access key refers to the access control credential used to authenticate and authorize data access requests, including API Key (Application Programming Interface Key) or token-based access tokens; abnormal call behavior includes the number of access requests exceeding a preset threshold in a short period of time, frequent calls to different data interfaces, requests initiated during non-business hours, or requests originating from abnormal IP addresses, etc.

[0088] For example, the server uses an API gateway component deployed at the platform boundary to monitor all incoming data access requests in real time and sends the request information to the behavior analysis module. This module creates an access behavior profile for each access key, recording multi-dimensional indicators such as access frequency, API call type, geographical location, and access time. Based on a defined access anomaly rule model, the server continuously assesses the security status of the current access behavior and links the assessment results with the key lifecycle management module.

[0089] In the key lifecycle management module, the server is configured with a key status table and a rotation policy: when the running time of a certain access key reaches a set period (such as 72 hours), the rotation logic will be triggered, a replacement key will be generated, and the data access party will be notified to update it; when the access behavior is detected to match the preset "medium" or "severe" risk level rules, such as initiating more than 100 query requests or calling multiple sensitive data field interfaces within one minute, the server will immediately suspend the access key's usage rights, call the key destruction service to update its status to "revoked", and completely delete it from the key database to prevent it from being exploited or brute-forced in the future.

[0090] In addition, the server will also record the abnormal behavior event in the audit log controlled by the blockchain smart contract, forming an immutable chain of access violations for subsequent security audits and platform management.

[0091] In this embodiment, by introducing a dynamic access key rotation mechanism and a behavior monitoring linkage strategy, real-time risk perception and responsive access control of data access behavior are achieved. Compared with the traditional static key configuration method, the validity of the key can be automatically adjusted according to changes in access behavior, effectively preventing data security threats caused by key leakage, interface abuse, or malicious scanning. Combined with abnormal behavior detection and key destruction mechanisms, the platform's ability to block potential attack paths is improved, enhancing the access control precision and dynamic security protection capabilities during the power trading data sharing process.

[0092] In an exemplary embodiment, step S201, which performs a dynamic rotation operation on the access key corresponding to the data access party, further includes: determining the leakage risk level corresponding to the access key based on the security status of the access key; determining the corresponding rotation frequency based on the leakage risk level; and performing a dynamic rotation operation on the access key according to the rotation frequency.

[0093] Among them, security status refers to the comprehensive assessment result of the risk exposed by the access key during the current operating cycle. The assessment basis includes behavioral indicators such as access frequency, call failure rate, source IP change, and access during non-business periods; leakage risk level is the platform's classification of access keys into three levels of leakage risk: minor leakage risk, moderate leakage risk, and severe leakage risk, based on the security status judgment result, to implement differentiated control strategies for different levels of key risk; rotation frequency refers to the automatic replacement cycle set for keys of different risk levels. The higher the risk level, the shorter the rotation frequency.

[0094] For example, the server continuously collects behavioral data on access keys and inputs it into the security analysis module for risk scoring. A preset risk threshold is used: scores between 0 and 0.3 are marked as minor risk of data leakage, with a corresponding rotation period of 24 hours; scores between 0.3 and 0.7 are marked as moderate risk of data leakage, with a rotation period of 6 hours; and scores above 0.7 are marked as severe risk of data leakage, with a rotation period of 1 hour.

[0095] When a key reaches its designated rotation time, the server automatically invokes the key management module to generate a new access key, update the key mapping table, and mark the old key as "in disuse," setting a short-term concurrent validity period to support session migration. Simultaneously, the server securely distributes the new key to the data access party via an encrypted channel, recording the entire rotation process and the association information between the old and new keys in the key audit log to ensure the verifiability and closed-loop operation of the key change process.

[0096] In this embodiment, by combining real-time monitoring of access behavior with an automatic risk level classification mechanism, a strategy for dynamically controlling the key lifecycle based on leakage risk is constructed. This strategy can quickly adjust the key rotation frequency according to the access security situation, thereby shortening the exposure window of high-risk keys and enhancing the ability to respond quickly to potential attack paths. Simultaneously, the key update logic triggered by the rotation frequency improves the execution accuracy and resource scheduling efficiency of the rotation mechanism, balancing security and system performance, and significantly enhancing the security resilience and management precision of the power trading data platform in environments with multi-source data access and frequent access.

[0097] In an exemplary embodiment, determining the leakage risk level corresponding to the access key based on the security status of the access key further includes: performing statistical analysis on the access behavior of the data access party to determine the behavioral statistics information corresponding to the access behavior; the behavioral statistics information includes at least the access request frequency, access time distribution, access network address distribution, call failure rate, and access path range; and determining the leakage risk level corresponding to the access key based on the behavioral statistics information.

[0098] Among them, behavioral statistics refer to the set of access characteristics used to characterize the data access party within a specific time period, reflecting whether there are abnormal access patterns; access request frequency refers to the number of key calls per unit time; access time distribution refers to the degree of concentration of the time when the calls occur, whether they are concentrated in business hours or there are high-frequency accesses late at night; access network address distribution refers to whether the geographical or organizational distribution of the IP addresses of the request source is stable; call failure rate reflects whether there are a large number of invalid attempts or suspected probing behavior; access path range indicates whether the calling interface is unauthorized, such as accessing unauthorized interfaces or paths not disclosed by the probing platform.

[0099] For example, the server continuously records the operation logs of each access key during runtime, and the log analysis engine aggregates and analyzes the access behavior at fixed intervals (such as hourly). In the statistical results, if a key initiates more than 50 requests within 5 minutes, calls to interfaces across multiple business domains, frequently switches IPs, and has a call failure rate higher than 20%, this behavior pattern will be judged as "moderate risk of data leakage"; while if the requests are concentrated between 0:00 and 4:00 AM, the IP addresses come from multiple countries or anonymous proxy nodes, and the access path contains unauthorized interfaces, the server can assess it as "severe risk of data leakage".

[0100] The server takes the above-mentioned behavioral statistics as input, and submits them to the risk assessment model to calculate a comprehensive risk score. The score is then mapped to a preset risk level range, and finally a leakage risk level label associated with the access key is generated, providing a basis for decision-making for subsequent dynamic rotation or key destruction operations.

[0101] In this embodiment, by introducing multi-dimensional behavioral statistics as the core basis for assessing the security status of access keys, the identification of access risks has shifted from static rules to dynamic behavioral modeling, accurately capturing potential malicious access patterns and unauthorized usage behaviors. The behavioral statistics indicator system covers multiple dimensions such as access frequency, time, source, and path, providing a rich data foundation for classifying the risk level of access key leakage. This effectively improves the platform's accuracy in identifying sensitive keys and its automated protection capabilities in complex access environments, providing reliable support for subsequent key rotation and access control strategies.

[0102] In one exemplary embodiment, such as Figure 3As shown in the figure, this application provides a privacy protection and data encryption system for the power trading platform, which operates in the power trading platform and specifically includes five major modules. Among them,

[0103] Module 1: Use blockchain technology to build a decentralized trading network and construct a distributed ledger. Upload key data of transaction records and contract terms to the blockchain, use the hash algorithm to ensure data immutability, and use smart contracts to automatically execute privacy policies. Combine the trusted execution environment and multi-party secure computation to achieve joint analysis of data in an encrypted state.

[0104] Among them, the hash algorithm is specifically: convert an input of any length into an output of a fixed length through a mathematical function, and its general formula can be expressed as: h = H(m); where m is the input data, H is the hash function, and h is the hash value of a fixed length;

[0105] In addition, the server integrates a smart contract module in the blockchain to achieve automatic execution of privacy policies in power trading, and combines the trusted execution environment (Trusted Execution Environment, TEE) and multi-party secure computation (Multi-Party Computation, MPC) technologies to achieve joint analysis of data in a ciphertext state and prevent plaintext exposure.

[0106] Module 2: Adopt a cloud-edge-end collaborative encryption transmission method. On the one hand, use end-to-end encryption technology for the quotes and transaction information of real-time spot trading data, ensure the security of the transmission process through the SSL / TLS protocol, and introduce the AES-256 lightweight encryption algorithm to reduce latency for highly sensitive user identities and transaction amounts to adapt to high-frequency trading scenarios. Data encryption transmission needs to combine the asymmetric encryption algorithm RSA and collaborative strategies to ensure secure interaction between the terminal, edge node, and cloud. The specific formula is as follows:

[0107] 1. Key generation

[0108] 1.1 Modulus calculation: n = p × q, where p and q are large prime numbers, and n is part of the public key;

[0109] 1.2 Euler's totient function calculation: Ф(n) = (p - 1) × (q - 1);

[0110] 1.3 Public key and private key generation: Public key e: satisfies 1 < e < Ф(n) and is relatively prime to Ф(n);

[0111] Private key d: satisfies e × d ≡ 1 mod Ф(n), that is, d is the modular inverse of e;

[0112] 2. Encryption process: Terminal / edge device → cloud: c = m emod n, where m is plaintext and c is ciphertext;

[0113] 3. Decryption process: Cloud / Edge node → Terminal: m=c d mod n.

[0114] Module 3 employs data anonymization and desensitization methods to dynamically anonymize sensitive information such as user identifiers and geographic locations. It utilizes hash value replacement and differential privacy injection to prevent data tracing attacks and uses zero-knowledge proofs to verify the legality of transactions.

[0115] Among them, dynamic desensitization is a method of desensitizing data by using edge computing during the cloud-edge-device collaborative encrypted transmission process. The desensitization engine is deployed at the edge node close to the data source to dynamically mask the user identity and geolocation fields, retaining the first 3 characters and hiding the subsequent characters.

[0116] The desensitization process employs randomized desensitization, as detailed below:

[0117] Noisy perturbation numerical data: x'=x+ε where ε~N(0, σ) 2 Add Gaussian noise, where ε is the noise variable, following a constant with a mean of 0 and a mean of σ. 2 The variance follows a normal distribution, and σ controls the disturbance intensity, preserving the statistical distribution but obscuring the true value;

[0118] Random permutation: x'=shuffle(x1, x2, ..., x) n This function shuffles the data within a column, disrupting the direct association between the original data record and the identity entity.

[0119] Anonymization employs K-anonymization: Data sets D containing quasi-identifiers (QIs) are anonymized. Specifically, for any record, its QI attribute combination has at least k-1 other records in the dataset with the same value, i.e., ∀QI∈D, count(QI)≥k. This can be achieved through generalization (e.g., generalizing a specific age to an age range) or suppression (e.g., hiding some fields), making sensitive information "indistinguishable" within the group and reducing the risk of re-identification.

[0120] In addition, the server introduces zero-knowledge proof technology in the result sharing stage to verify the legitimacy of the de-identified data without exposing the original data, ensuring that the shared results are authentic and valid.

[0121] Module 4 adopts a dynamic permission revoke mechanism for power trading data and an automated key lifecycle management method. It monitors data access behavior in real time through the API gateway, triggers automatic permission revoke for abnormal operations with excessive query frequency, and links the blockchain to record audit logs. At the same time, it uses HSM hardware to centrally manage the root key, supports automatic key rotation, and performs emergency destruction when a brute-force attack is detected.

[0122] In the automated key lifecycle management process, key leakage levels are classified into three levels: minor leakage risk, moderate leakage risk, and severe leakage risk. For minor leakage risk, the automatic key rotation frequency is controlled at once every 24 hours; for moderate leakage risk, the automatic key rotation frequency is controlled at once every 6 hours; and for severe leakage risk, the automatic key rotation frequency is controlled at once every hour. Targeted real-time monitoring and processing are carried out for this type of problem.

[0123] Module 5 is used to implement a secure data sharing method for electricity trading data. The electricity trading platform serves as the central information carrier. The parties that trade with the electricity trading platform have the right to control the electricity trading data. When a party needs to share the electricity trading data with others, it sends a request to the electricity trading platform center. The electricity trading platform conducts a security assessment of the sharer through the background and credit data, and decides whether to share the data based on the assessment results.

[0124] Specifically, during the security assessment of the sharing party through the background and credit data, if the sharing party poses a security risk, the sharing request of the transaction object will be rejected. If the sharing party does not pose a security risk, a single key generation mechanism will be adopted. During data sharing, a unique dynamic key will be generated for each transmission. The data receiver can only decrypt the data once with this key. After use, the key will automatically become invalid, ensuring that the data cannot be reused after decryption.

[0125] The sharing of electricity spot trading data is carried out through the electricity trading platform. A decentralized trading network is built using blockchain technology to transmit the data. At the same time, cloud-edge-device collaborative encrypted transmission, data desensitization and anonymization, dynamic permission eviction mechanism for electricity trading data, and automated key lifecycle management are used to protect the data sharing process.

[0126] like Figure 4The diagram illustrates the process of implementing the privacy protection and data encryption methods of the aforementioned power trading platform privacy protection and data encryption system. This includes: using blockchain technology to construct a decentralized trading network for data transmission; simultaneously employing cloud-edge-device collaborative encryption transmission, data desensitization and anonymization, a dynamic permission revoke mechanism for power trading data, and automated key lifecycle management for protective data sharing; if the sharer poses a security risk, the sharing request from the trading entity is rejected; if the sharer does not pose a security risk, a single-use key generation mechanism is adopted. During data sharing, a unique dynamic key is generated for each transmission. The data receiver can only decrypt the data once using this key, and the key automatically expires after use, ensuring that the data cannot be reused after decryption.

[0127] In this embodiment, a decentralized trading network is constructed using blockchain technology to transmit data. Simultaneously, a cloud-edge-device collaborative encrypted transmission method, data desensitization and anonymization methods, a dynamic permission revoke mechanism for electricity trading data, and automated key lifecycle management are used for protective data sharing. When a trading entity needs to share electricity trading data with others, it sends a request to the electricity trading platform center. The electricity trading platform conducts a security assessment of the sharer through its backend, along with credit data, and decides whether to share the data based on the assessment results. This improves the security of electricity spot trading data. Specifically, this solution processes electricity trading data through five modules. Firstly... By constructing a decentralized trading network using blockchain technology, a secure data network is built for secure data transmission. Then, through cloud-edge-device collaborative encrypted transmission, data desensitization and anonymization, and a dynamic permission revocation mechanism for electricity trading data, data is securely encrypted, desensitized, anonymized, and protected during data transmission. This ensures the secure confidentiality of transaction-generated data, guaranteeing effective protection throughout the entire generation and transmission process. Furthermore, the designed secure data sharing method for electricity trading data employs an audit system to conduct security audits of sharers, determining whether data sharing is permitted based on the audit results, further enhancing data security.

[0128] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0129] Based on the same inventive concept, this application also provides a power transaction data security processing device for implementing the aforementioned power transaction data security processing method. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more power transaction data security processing device embodiments provided below can be found in the limitations of the power transaction data security processing method described above, and will not be repeated here.

[0130] In one exemplary embodiment, such as Figure 5 As shown, a secure processing device for electricity transaction data is provided, comprising: a transaction data generation module 501, a transaction data storage module 502, a transaction data desensitization module 503, and a transaction data sharing module 504, wherein:

[0131] The transaction data generation module 501 is used to respond to the electricity transaction request from the user and complete the transaction matching operation in the pre-built blockchain transaction network to generate electricity transaction data corresponding to the electricity transaction request.

[0132] The transaction data storage module 502 is used to encrypt and transmit power transaction data to the cloud of the power transaction data security processing platform for storage through a cloud-edge-device collaborative architecture.

[0133] The transaction data anonymization module 503 is used to respond to a request for sharing electricity transaction data, retrieve electricity transaction data from the cloud, and perform anonymization and desensitization processing on the electricity transaction data to obtain anonymized electricity transaction data.

[0134] The transaction data sharing module 504 is used to perform a security assessment on the receiving end of the sharing request. If the security assessment result is passed, the de-identified data is encrypted to obtain encrypted de-identified data of the power transaction data, and the encrypted de-identified data is transmitted to the receiving end.

[0135] In one embodiment, the aforementioned transaction data storage module 502 is further configured to, when the power transaction data is transmitted to the edge node, identify and determine sensitive information in the power transaction data at the edge node; perform dynamic data masking on the sensitive information in the power transaction data to obtain desensitized power transaction data; perform encryption processing on the desensitized power transaction data to obtain encrypted data; and upload the encrypted data to the cloud for storage.

[0136] In one embodiment, the transaction data sharing module 504 is further configured to generate a one-time dynamic key for this data transmission; use the one-time dynamic key to encrypt the de-identified data to obtain encrypted de-identified data of the power transaction data; and transmit the encrypted de-identified data and the one-time dynamic key to the receiving end through an encrypted channel respectively.

[0137] In one embodiment, the aforementioned power transaction data security processing device further includes a key dynamic management module, which is used to perform dynamic rotation operations on the access keys corresponding to the data access party, and monitor the access behavior of the data access party to the power transaction data in real time through the gateway; if abnormal query frequency or abnormal call behavior is detected in the access behavior, the access key corresponding to the data access party is destroyed.

[0138] In one embodiment, the aforementioned key dynamic management module is further configured to determine the leakage risk level corresponding to the access key based on the security status of the access key; determine the corresponding rotation frequency based on the leakage risk level; and perform dynamic rotation operation on the access key according to the rotation frequency.

[0139] In one embodiment, the aforementioned key dynamic management module is further used to perform statistical analysis on the access behavior of the data access party and determine the behavioral statistics information corresponding to the access behavior; the behavioral statistics information includes at least the access request frequency, access time distribution, access network address distribution, call failure rate, and access path range; based on the behavioral statistics information, the leakage risk level corresponding to the access key is determined.

[0140] Each module in the aforementioned secure processing device for electricity trading data can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0141] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores electricity trading data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network. When executed by the processor, the computer program implements a secure method for processing electricity trading data.

[0142] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0143] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0144] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0145] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0146] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0147] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0148] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0149] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for securely processing electricity transaction data, characterized in that, The method includes: In response to a user's electricity trading request, the system completes the transaction matching operation in a pre-built blockchain trading network and generates electricity trading data corresponding to the electricity trading request. Through a cloud-edge-device collaborative architecture, the power trading data is encrypted and transmitted to the cloud of the power trading data security processing platform for storage. In response to a request to share the power trading data, the power trading data is retrieved from the cloud, and the power trading data is desensitized and anonymized to obtain desensitized power trading data. A security assessment is performed on the receiving end of the sharing request. If the security assessment result is passed, the de-identified data is encrypted to obtain encrypted de-identified data of the power transaction data, and the encrypted de-identified data is transmitted to the receiving end.

2. The method according to claim 1, characterized in that, The process of encrypting and transmitting the power trading data to the cloud of the power trading data security processing platform for storage, through a cloud-edge-device collaborative architecture, includes: When the power trading data is transmitted to the edge node, sensitive information in the power trading data is identified and determined at the edge node. The sensitive information in the power trading data is dynamically masked to obtain desensitized power trading data; The de-identified power transaction data is encrypted to obtain encrypted data; The encrypted data is uploaded to the cloud for storage.

3. The method according to claim 1, characterized in that, The step of encrypting the de-identified data to obtain encrypted de-identified data of the power transaction data, and transmitting the encrypted de-identified data to the receiving end, includes: Generate a one-time dynamic key for this data transmission; The de-identified data is encrypted using the one-time dynamic key to obtain the encrypted de-identified data of the power transaction data; The encrypted and desensitized data and the one-time dynamic key are transmitted to the receiving end through an encrypted channel.

4. The method according to claim 1, characterized in that, The method further includes: Dynamically rotate the access key corresponding to the data access party, and monitor the access behavior of the data access party to the power transaction data in real time through the gateway; If any abnormal query frequency or abnormal call behavior is detected in the access behavior, the access key corresponding to the data access party will be destroyed.

5. The method according to claim 4, characterized in that, The dynamic rotation operation of the access key corresponding to the data access party includes: Based on the security status of the access key, determine the leakage risk level corresponding to the access key; Based on the leakage risk level, a corresponding rotation frequency is determined, and the access key is dynamically rotated according to the rotation frequency.

6. The method according to claim 5, characterized in that, The step of determining the leakage risk level corresponding to the access key based on the security status of the access key includes: Statistical analysis is performed on the access behavior of the data access party to determine the corresponding behavioral statistics; the behavioral statistics include at least access request frequency, access time distribution, access network address distribution, call failure rate, and access path range; Based on the behavioral statistics, the leakage risk level corresponding to the access key is determined.

7. A secure processing device for electricity transaction data, characterized in that, The device includes: The transaction data generation module is used to respond to the electricity transaction request from the user and complete the transaction matching operation in the pre-built blockchain transaction network to generate electricity transaction data corresponding to the electricity transaction request. The transaction data storage module is used to encrypt and transmit the power transaction data to the cloud of the power transaction data security processing platform for storage through a cloud-edge-device collaborative architecture; The transaction data anonymization module is used to respond to a sharing request for the electricity transaction data, retrieve the electricity transaction data from the cloud, and perform anonymization and desensitization processing on the electricity transaction data to obtain anonymized data of the electricity transaction data; The transaction data sharing module is used to perform a security assessment on the receiving end of the sharing request. If the security assessment result is passed, the de-identified data is encrypted to obtain encrypted de-identified data of the power transaction data, and the encrypted de-identified data is transmitted to the receiving end.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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