Cross-domain mutual trust identification authentication platform for power terminal and multi-service system

Abstract

The invention relates to the technical field of electric power information, in particular to a cross-domain mutual trust identification authentication platform for an electric power terminal and a multi-service system. The system comprises twelve functional modules such as an authentication request receiving module, an identifier generating module and an authentication processing module. The authentication request receiving module is used for receiving and forwarding an authentication request; the identifier generation module generates a unique identifier through the terminal identifier, the random salt value and the hash value of the previous block; the authentication processing module calculates authentication parameters based on the system key, the current timestamp and the terminal behavior characteristics. According to the platform, an edge calculation module is used for preprocessing terminal behavior characteristics, a machine learning algorithm is introduced to realize risk assessment, a quantum encryption technology is used for key management, a deep learning algorithm is used for anomaly detection, and an authentication strategy can be adjusted in real time according to a risk assessment result. According to the platform, through multi-dimensional verification and intelligent analysis, safe and credible authentication between the power terminal and the multi-service system is realized, and illegal access and data tampering are effectively prevented.

Description

Technical Field

[0001] The present invention relates to the field of electric power information technology, and in particular to a cross-domain mutual trust identification authentication platform for electric power terminals and multi-business systems. Background Art

[0002] With the continuous development and intelligent upgrading of power systems, the number and types of power terminals are increasing, and the interaction with multi-service systems is becoming more frequent and complex. In this context, ensuring the safe and reliable interaction between power terminals and multi-service systems has become a crucial issue.

[0003] Traditional authentication methods often have many limitations. For example, the authentication security is insufficient, and it is easy to be attacked by illegal terminal access and data tampering; there is a lack of effective risk assessment mechanism, which makes it difficult to detect and respond to potential security threats in advance; it has poor adaptability to different types of power terminals and diversified business needs; the authentication efficiency is low and cannot meet the real-time requirements; the application of biometric recognition technology is insufficient, and the authentication accuracy and reliability need to be improved; the key management is not advanced enough, and the security and timeliness of the system key are difficult to guarantee; there is a lack of dynamic authentication strategy adjustment mechanism, and the authentication strategy cannot be optimized in time according to business changes and security situation; the anomaly detection capability is weak, and it is difficult to effectively discover and handle abnormal behavior in the authentication process; the log record and terminal information management are not perfect, which is not conducive to subsequent auditing and troubleshooting; cross-domain mutual trust is difficult to achieve, which restricts the integration and intelligent development of the power system. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to solve the many limitations of traditional authentication methods, such as insufficient authentication security, easy access to illegal terminals and data tampering attacks; lack of an effective risk assessment mechanism, difficulty in early detection and response to potential security threats; poor adaptability to different types of power terminals and diversified business needs; low authentication efficiency and inability to meet real-time requirements; insufficient application of biometric recognition technology, and the need to improve authentication accuracy and reliability; insufficient advanced key management, and difficulty in ensuring the security and timeliness of system keys; lack of a dynamic authentication strategy adjustment mechanism, and inability to optimize authentication strategies in a timely manner according to business changes and security trends; weak anomaly detection capabilities, and difficulty in effectively discovering and handling abnormal behaviors during the authentication process; imperfect log recording and terminal information management, which is not conducive to subsequent auditing and troubleshooting; and cross-domain mutual trust is difficult to achieve, which restricts the integration and intelligent development of the power system.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a cross-domain mutual trust identification authentication platform method for a power terminal and a multi-business system, which includes an authentication request receiving module, an identification generation module, an authentication processing module, an authentication result determination module, a risk assessment module, a biometric identification module, an edge computing module, a key management module, a log recording module, a terminal information management module, an authentication policy configuration module, and an anomaly detection module;

[0008] The authentication request receiving module is used to receive the authentication request of the power terminal and pass the request to the identification generating module and the authentication processing module;

[0009] The identification generation module is used to generate a unique identification based on the terminal identification, the random salt value and the hash value of the previous block;

[0010] The authentication processing module is used to calculate authentication parameters based on the system key, the current timestamp and the terminal behavior characteristics.

[0011] As a preferred solution of the cross-domain mutual trust identification authentication platform method of the power terminal and the multi-business system described in the present invention, wherein: the authentication result determination module compares the authentication parameters with the preset threshold to determine the authentication result; the risk assessment module evaluates the authentication risk through a machine learning algorithm; the biometric recognition module is used to verify the biometrics; and the edge computing module is used to perform preliminary processing of the terminal behavior characteristics.

[0012] As a preferred solution of the cross-domain mutual trust identification authentication platform method of the power terminal and the multi-business system described in the present invention, wherein: the key management module uses quantum encryption technology to regularly update the system key according to the system key and the update factor; the log recording module records the authentication process data; the terminal information management module stores and manages the terminal information; the authentication policy configuration module dynamically adjusts the authentication policy according to the risk assessment results.

[0013] As a preferred solution of the cross-domain mutual trust identification authentication platform method of the power terminal and the multi-business system described in the present invention, wherein: the anomaly detection module adopts a deep learning algorithm to perform abnormal behavior detection based on historical abnormal data and real-time authentication process data.

[0014] As a preferred solution of the cross-domain mutual trust identification authentication platform method between the power terminal and the multi-business system described in the present invention, when the authentication parameter is greater than the preset threshold, the authentication is judged to be successful; when the authentication parameter is less than or equal to the preset threshold, the authentication is judged to be failed.

[0015] As a preferred solution of the cross-domain mutual trust identification authentication platform method of the power terminal and the multi-business system described in the present invention, the preliminary processing results of the edge computing module are fed back to the authentication processing module and the risk assessment module in real time.

[0016] As a preferred solution of the cross-domain mutual trust identification authentication platform method between the power terminal and the multi-business system described in the present invention, wherein: the authentication parameters calculated by the authentication processing module are sent to the authentication result determination module, the authentication result determination module feeds back the result to the authentication request receiving module, and at the same time, the risk assessment module obtains data from the authentication processing module for assessment, and transmits the assessment result to the authentication policy configuration module.

[0017] As a preferred solution of the cross-domain mutual trust identification authentication platform method between the power terminal and the multi-business system described in the present invention, the biometric recognition module sends the recognition result to the authentication processing module, and the edge computing module passes the terminal behavior characteristics to the authentication processing module and the risk assessment module after preliminary processing of the data.

[0018] As a preferred solution of the cross-domain mutual trust identification authentication platform method of the power terminal and the multi-business system described in the present invention, wherein: the terminal information management module interacts with the authentication processing module and the authentication result determination module to store and manage terminal information.

[0019] As a preferred solution of the cross-domain mutual trust identification authentication platform method between the power terminal and the multi-business system described in the present invention, wherein: the authentication policy configuration module adjusts the strategy according to the results of the risk assessment module, the requirements of the multi-business system and the changes in the security level of the power terminal, and passes the strategy to the relevant modules, and the anomaly detection module obtains data from each module for detection and feeds back the results to the relevant modules.

[0020] The beneficial effects of the present invention are as follows: by integrating the identification generation mechanism of terminal identification, random salt value and block hash value, and combining the triple authentication mechanism of system key, timestamp and terminal behavior characteristics, all-round verification of the identity of the power terminal is achieved, illegal terminal access and data tampering are effectively prevented, and authentication security is significantly improved.

[0021] By deploying edge computing modules on the terminal side for feature preprocessing and introducing machine learning algorithms for risk assessment, the system has the ability to intelligently identify abnormal behaviors and warn of risks, shifting security protection from passive defense to active prevention. At the same time, the introduction of edge computing reduces data transmission volume and improves authentication efficiency.

[0022] By using quantum encryption technology to dynamically update keys, combined with adjustable authentication strategies and deep learning anomaly detection, an adaptive security protection system has been built. The system can adjust protection strategies in real time according to business needs and security trends, ensuring the long-term safe operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 A flow chart of a cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems;

[0025] Figure 2 A computer device diagram for a cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems;

[0026] Figure 3 The schematic diagram of the platform composition of the cross-domain mutual trust identification and authentication platform method for power terminals and multi-business systems is shown in FIG. DETAILED DESCRIPTION

[0027] 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.

[0028] 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.

[0029] 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 is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0030] Example 1

[0031] Reference Figure 1-2 , which is the first embodiment of the present invention, and provides a cross-domain mutual trust identification authentication platform method for a power terminal and a multi-service system, including:

[0032] S100: authentication request receiving module, identification generation module, authentication processing module, authentication result determination module, risk assessment module, biometric identification module, edge computing module, key management module, logging module, terminal information management module, authentication policy configuration module and anomaly detection module;

[0033] In the embodiment of the present application, the authentication request receiving module serves as the entrance of the platform and is responsible for receiving authentication requests from various power terminals. These power terminals include but are not limited to: smart meters, power distribution terminals, power consumption information collection terminals, power monitoring terminals, etc. The authentication request usually contains basic information such as terminal identification, authentication timestamp, authentication type, etc.

[0034] Specifically, when the power terminal initiates an authentication request, the authentication request receiving module first performs format check and basic verification on the request data. The format check includes checking the integrity of the request message and the validity of the data field; the basic verification includes verifying the legitimacy of the request source IP address and the validity of the request timestamp. Only requests that pass these two links will be forwarded to the subsequent modules for processing.

[0035] In an optional embodiment, the authentication request receiving module can also implement a request flow control function. For example, when it is detected that a certain IP address initiates a large number of authentication requests in a short period of time, the system will automatically start a flow limiting mechanism, requiring that the request frequency of the IP address must not exceed a preset threshold (such as no more than 10 requests per second). This mechanism can effectively prevent potential DDoS attacks and protect the stable operation of the platform.

[0036] In an optional embodiment, the authentication request receiving module can also implement request queue management based on terminal type and service priority. For example, authentication requests for important power distribution equipment can be processed first; requests from ordinary power consumption information collection terminals are processed according to the first-in-first-out principle. In specific implementation, multiple priority queues can be set:

[0037] Priority queue example:

[0038] Highest priority: substation automation equipment, trunk line monitoring equipment; Highest priority: distribution automation terminals, key user energy metering devices; Normal priority: ordinary smart meters, general electricity consumption information collection terminals; Low priority: testing equipment, temporary access equipment.

[0039] It should be noted that the authentication request receiving module must not only ensure timely processing of requests, but also ensure the traceability of the processing process. To this end, the module will record detailed information for each request, including:

[0040] Request timestamp (accurate to milliseconds); terminal identification information (including hardware serial number, MAC address, etc.); request source (IP address, network access point); request type (first authentication, re-authentication, periodic authentication, etc.); processing status (received, forwarded, rejected, etc.); processing time (the time interval from request receipt to forwarding).

[0041] S101: The key management module uses quantum encryption technology to regularly update the system key according to the system key and the update factor; the log recording module records the authentication process data; the terminal information management module stores and manages the terminal information; the authentication policy configuration module dynamically adjusts the authentication policy according to the risk assessment results.

[0042] S102: The anomaly detection module uses a deep learning algorithm to detect abnormal behavior based on historical anomaly data and real-time authentication process data.

[0043] S103: The preliminary processing results of the edge computing module are fed back to the authentication processing module and the risk assessment module in real time.

[0044] S104: The biometric recognition module sends the recognition result to the authentication processing module. After the edge computing module preliminarily processes the data, it passes the terminal behavior characteristics to the authentication processing module and the risk assessment module.

[0045] S200: wherein the authentication request receiving module is used to receive the authentication request of the power terminal and pass the request to the identification generating module and the authentication processing module;

[0046] In the embodiment of the present application, the authentication request receiving module uses a message queue as middleware to transmit the request to ensure the reliability of data transmission. After receiving the request, the authentication request receiving module first verifies the format and basic information of the request, including checking the integrity of the request message, verifying the legitimacy of the terminal identification, and verifying the validity of the timestamp. After the verification is passed, the request is packaged and sent to the identification generation module and the authentication processing module respectively, and the TLS1.3 protocol is used during the sending process to ensure transmission security.

[0047] Specifically, when processing a request, the authentication request receiving module will record the following key information: terminal identification (including device serial number, MAC address), request timestamp (accurate to milliseconds), request type (such as first authentication, re-authentication, etc.), request source (access point information), network environment parameters (such as signal strength, network type), etc. This information will serve as an important basis for subsequent authentication processing.

[0048] In an optional embodiment, the authentication request receiving module can also implement priority-based request hierarchical processing. Requests are divided into different priorities based on factors such as terminal type and business importance. For example, the authentication request of the substation control terminal can be given the highest priority, while the request of the ordinary power consumption information collection terminal is given an ordinary priority. Through this hierarchical mechanism, timely response to key businesses is ensured.

[0049] It should be noted that the authentication request receiving module needs to ensure the integrity and traceability of data during the request transmission process. To this end, the module will generate a unique request identifier for each request and maintain the consistency of the identifier in each link of the request transmission. At the same time, the module will also record the complete processing link of the request, including the receiving time, processing time, forwarding time, etc., to facilitate subsequent audits and problem location.

[0050] S201: The authentication result determination module compares the authentication parameters with the preset threshold to determine the authentication result; the risk assessment module evaluates the authentication risk through a machine learning algorithm; the biometric recognition module is used to verify the biometrics; and the edge computing module is used to perform preliminary processing on the terminal behavior characteristics.

[0051] S202: When the authentication parameter is greater than a preset threshold, the authentication is determined to be successful; when the authentication parameter is less than or equal to the preset threshold, the authentication is determined to be failed.

[0052] S203: The authentication parameters calculated by the authentication processing module are sent to the authentication result determination module, and the authentication result determination module feeds back the result to the authentication request receiving module. At the same time, the risk assessment module obtains data from the authentication processing module for assessment and transmits the assessment result to the authentication policy configuration module.

[0053] S300: an identification generation module, used to generate a unique identification according to the terminal identification, a random salt value and a hash value of a previous block;

[0054] In the embodiment of the present application, the identification generation module adopts a layered structure design, which consists of a basic information layer, a random processing layer and a blockchain layer. The basic information layer is responsible for processing terminal identification information, including hardware serial number, MAC address, device type, etc.; the random processing layer uses a hardware random number generator to generate high-quality random salt values; the blockchain layer is responsible for maintaining and providing the hash value information of the previous block. The three layers of data are combined through a specific algorithm to finally generate a unique identification.

[0055] Specifically, the identification generation process first normalizes the terminal identification to ensure a uniform format; then generates a 32-byte random salt value and obtains the hash value of the previous block; finally, these three parts of data are combined and hashed according to a predetermined algorithm to obtain the final unique identification. The entire generation process is strictly controlled to be completed within 10 milliseconds.

[0056] In an optional embodiment, the identification generation module can use different hash algorithms according to the security requirements of the terminal. For general terminals, the SHA-256 algorithm is used; for terminals with higher security requirements, the SHA3-512 algorithm is used; for terminals that need to meet national encryption standards, the SM3 algorithm is used. The selection of different algorithms is determined by the security level configuration of the terminal.

[0057] It should be noted that the identification generation process must ensure the uniqueness and unpredictability of the generated identification. To this end, the module will add additional random factors, such as precise timestamps, environmental noise, etc., to increase the randomness of the identification. At the same time, the module will also maintain an identification history library to ensure the uniqueness of the generated identification through a duplicate checking mechanism.

[0058] S400: an authentication processing module, used to calculate authentication parameters according to a system key, a current timestamp and terminal behavior characteristics.

[0059] In the embodiment of the present application, the authentication processing module adopts a three-layer verification mechanism: the first layer is the identity authentication based on the system key, which verifies the key information held by the terminal; the second layer is the timeliness verification based on the timestamp to prevent replay attacks; the third layer is the behavior authentication based on the terminal behavior characteristics to identify abnormal behavior patterns. The results of these three layers of verification are weighted and calculated to obtain the final authentication parameters.

[0060] Specifically, the authentication processing module first verifies the key information provided by the terminal, including the validity and integrity of the key; then checks the validity of the timestamp, requiring that the deviation between the terminal time and the system time does not exceed the preset threshold; and finally analyzes the behavioral characteristics of the terminal, including access frequency, data transmission mode, operation sequence, etc. The module calculates these verification results according to the preset weights and obtains an authentication parameter between 0 and 1.

[0061] In an optional embodiment, the authentication processing module can dynamically adjust the weight of each verification result. For example, when the network environment is detected to be unstable, the weight of the timestamp verification can be appropriately reduced; when a certain type of terminal is found to have batch abnormalities, the weight of the behavior feature verification can be increased. This dynamic adjustment mechanism can improve the adaptability and accuracy of authentication.

[0062] It should be noted that the authentication processing module needs to maintain complete authentication process records. Each authentication will record the detailed verification process, including the specific results of each verification, the weight values ​​used, the final authentication parameters, etc. These records are not only used for subsequent audits and analysis, but also an important basis for dynamically adjusting authentication strategies. At the same time, the module also implements a complete exception handling mechanism, which can properly handle various abnormal situations that may occur during the authentication process to ensure the stability of the authentication service.

[0063] S401: The terminal information management module interacts with the authentication processing module and the authentication result determination module to store and manage terminal information.

[0064] S402: The authentication policy configuration module adjusts the policy according to the results of the risk assessment module, the requirements of the multi-business system and the changes in the security level of the power terminal, and passes the policy to the relevant modules. The anomaly detection module obtains data from each module for detection and feeds back the results to the relevant modules.

[0065] In summary, by setting up an identification generation mechanism based on terminal identification, random salt value and block hash value, each authentication request can generate a unique and unforgeable identification. This multi-factor integrated identification generation method not only ensures the uniqueness of the identification, but also realizes the traceability of the identification through blockchain technology, fundamentally preventing the access of illegal terminals.

[0066] By establishing a triple authentication mechanism of system key, timestamp and terminal behavior characteristics, multi-dimensional verification of terminal identity is achieved. The introduction of timestamp effectively prevents replay attacks, and behavior characteristic analysis can identify abnormal access behavior, significantly improving the security and reliability of authentication.

[0067] By deploying edge computing modules to perform preliminary processing of terminal behavior characteristics, data analysis tasks are moved to the terminal side, significantly reducing data transmission volume and network latency. This distributed processing architecture not only improves authentication efficiency, but also reduces the computing load of the central system.

[0068] By introducing the risk assessment module of machine learning algorithms, potential risks in the authentication process can be assessed in real time. This module can detect and warn security threats in advance through learning and analysis of historical data, shifting from passive defense to active prevention.

[0069] The key management mechanism based on quantum encryption technology is used to achieve secure update of system keys. This advanced key management solution not only ensures the security of keys, but also achieves dynamic evolution of keys through the introduction of update factors, effectively preventing the risk of key leakage.

[0070] By designing a dynamically adjustable authentication policy configuration module, the authentication policy can be adjusted in real time according to risk assessment results, business requirements and terminal security levels. This adaptive policy adjustment mechanism enables the platform to flexibly respond to security requirements in different scenarios and improves the adaptability of the system.

[0071] The anomaly detection module of the deep learning algorithm realizes the intelligent identification of abnormal behaviors in the authentication process. By analyzing historical abnormal data and real-time authentication data, the module can accurately identify abnormal patterns, issue warnings in time, and trigger protective measures.

[0072] The introduction of biometric recognition technology provides a higher level of security for important terminals. This multi-factor authentication solution not only improves the accuracy of authentication, but also enhances the anti-counterfeiting ability of the system.

[0073] Through the complete log record and terminal information management mechanism, the entire authentication process is traceable, which not only facilitates the subsequent audit and troubleshooting, but also provides data support for the optimization of security policies.

[0074] Through the coordination and cooperation among various functional modules, a complete cross-domain mutual trust system has been built. This systematic authentication solution breaks the limitations of traditional authentication, realizes the safe and reliable interaction between power terminals and multi-business systems, and lays the foundation for the intelligent development of power systems.

[0075] Example 2

[0076] Reference Figure 1 - Figure 3 , which is the second embodiment of the present invention. With the development of intelligence and digitization of power systems, the interaction between power terminals and multi-business systems is becoming increasingly frequent and complex. In order to ensure the secure transmission and legal access to data, it is crucial to establish an efficient and reliable cross-domain mutual trust identification and authentication platform. The cross-domain mutual trust identification and authentication platform between power terminals and multi-business systems proposed in the present invention aims to solve this problem, and its specific implementation method will be described in detail below.

[0077] This platform is mainly composed of an authentication request receiving module, an identification generation module, an authentication processing module, an authentication result determination module, a risk assessment module, a biometric identification module, an edge computing module, a key management module, a logging module, a terminal information management module, an authentication policy configuration module and an anomaly detection module. When the power terminal initiates an authentication request, the authentication request receiving module first receives the request and passes it to the identification generation module and the authentication processing module. The identification generation module generates a unique identification according to a preset algorithm, and the authentication processing module calculates authentication parameters based on system keys, terminal behavior characteristics, etc. The authentication result determination module compares the authentication parameters with the preset threshold to determine the authentication result. At the same time, the risk assessment module evaluates the risks in the authentication process, the biometric identification module performs biometric verification, the edge computing module performs preliminary processing, the key management module manages keys, the logging module records relevant data, the terminal information management module manages terminal information, the authentication policy configuration module configures and adjusts the authentication policy, and the anomaly detection module detects anomalies.

[0078] After receiving the authentication request from the power terminal, the authentication request receiving module sends the request to the identification generation module and the authentication processing module at the same time. After the identification generation module generates a unique identification, it passes it to the authentication processing module. The authentication processing module uses the identification from the identification generation module, the system key provided by the key management module, and the terminal behavior characteristics preliminarily processed and extracted by the edge computing module to calculate the authentication parameters and send the results to the authentication result determination module. The authentication result determination module compares the authentication parameters with the thresholds set and adjusted by the authentication policy configuration module to determine the authentication result and feeds the results back to the authentication request receiving module and other related modules (such as the logging module, the terminal information management module, etc.). The risk assessment module obtains relevant data from the authentication processing module, performs risk assessment, and passes the assessment results to the authentication policy configuration module and other modules that require risk information. The biometric recognition module sends the recognition results to the authentication processing module. After the edge computing module preliminarily processes the data, it passes the extracted terminal behavior characteristics to the authentication processing module and the risk assessment module.

[0079] The key management module provides the system key for the authentication processing module and updates the key according to the settings of the authentication policy configuration module. The logging module receives data from other modules (such as the authentication request receiving module, the authentication processing module, the authentication result determination module, etc.) for recording. The terminal information management module interacts with other modules (such as the authentication processing module, the authentication result determination module, etc.) to store and manage terminal information. The authentication policy configuration module adjusts the authentication policy according to the results of the risk assessment module, the requirements of the multi-business system, and the changes in the security level of the power terminal, and passes the policy to the relevant modules (such as the authentication processing module, the authentication result determination module, etc.). The anomaly detection module obtains data from each module for anomaly detection, and feeds back the detection results to the relevant modules for corresponding processing.

[0080] Identity generation module:

[0081] Unique_ID=Hash(ID terminal ||Salt)||Prev_Hash, in the identification generation module, by combining the terminal identification ID_{terminal} with the random salt value Salt, and processing it using the hash function Hash, and then connecting the hash value Prev_Hash of the previous block, a unique and difficult-to-forge identification Unique_ID is generated, which ensures that the identification of each terminal is highly unique and secure.

[0082] Authentication processing module:

[0083] Authentication_Parameter=f(ID terminal ,Keysystem , Timestamp, AI_Feature), according to the terminal identification ID_{terminal}, system key Key_{system}, current timestamp Timestamp and the terminal behavior feature AI_Feature extracted by the edge computing module, the preset authentication function f is used to calculate the authentication parameter Authentication_Parameter. The introduction of timestamp can prevent replay attacks, and combined with the terminal behavior characteristics can more comprehensively evaluate the reliability of authentication.

[0084] Authentication result determination module:

[0085] When Authentication_Parameter>Threshold, authentication is successful;

[0086] When Authentication_Parameter<=Threshold, authentication fails;

[0087] The authentication result determination module compares the calculated authentication parameter with the preset authentication threshold Threshold. If the authentication parameter is greater than the threshold, the authentication is successful; otherwise, the authentication fails. The threshold setting can be dynamically adjusted according to the system's security policy and actual needs.

[0088] Risk Assessment Module:

[0089] Risk_Assessmeng = ML(ID terminal The risk assessment module uses the machine learning algorithm ML to assess the potential risks in the authentication process based on the terminal ID_{terminal}, historical data Historical_Data and current behavior Current_Behavior. By learning and analyzing a large amount of historical data, it can accurately identify anomalies and potential security threats.

[0090] Key Management Module:

[0091] Key Management Module

[0092] The block uses quantum encryption technology Quantum_Encrypt to regularly update the system key based on the system key Key_{system} and update factor Update_Factor to ensure the security and timeliness of the key.

[0093] The logging module is based on:

[0094] Log_Entry = Compose(IDterminal ,Timestamp,Authentication_Parameter,Result,Blockchair

[0095] Record data;

[0096] Terminal information management module is based on:

[0097] Terminal_Info = {ID terminal , Attributes terminal , Unique_ID, AI_Profile}

[0098] Store and manage terminal information;

[0099] The authentication policy configuration module follows:

[0100] Policy=Set(Threshold, f, Update_Factor, Quantum_Parameters)

[0101] Configure the policy and:

[0102] Adjusted_Policy=Adjust(Policy, Requirement, Security_Level, AI_Recommendation)

[0103] Adjust strategies;

[0104] The anomaly detection module utilizes:

[0105] Anomaly=Deep_Learning(Authentication_Process_Data)

[0106] Detect anomalies.

[0107] Certification of common power terminals:

[0108] Implementation environment: The server is configured with 8-core CPU, 32GB memory, and the database is PostgreSQL database;

[0109] Data preparation: 100 common power terminals were selected, their device identification, MAC address and other information were collected, the initial system key was set, and the authentication threshold was determined to be 0.7;

[0110] Authentication process: The terminal sends an authentication request, the identifier generation module generates a unique identifier, the authentication processing module calculates the authentication parameters, assuming that the parameter of a certain terminal is 0.75, and the authentication result determination module determines that the authentication is successful;

[0111] Data recording and analysis: The log recording module records the authentication process data, and the terminal information management module updates the terminal authentication status;

[0112] The following is a table of authentication data for some terminals:

[0113] Terminal Number Authentication parameters Certification results 1 0.75 success 2 0.65 fail ... ... ...

[0114] Authentication success rate: 85%, average response time: 1.5 seconds.

[0115] Certification of high-risk power terminals:

[0116] Implementation environment: Enhance server performance with 16-core CPU, 64GB memory, and introduce more advanced encryption algorithms;

[0117] Data preparation: Identify 50 high-risk power terminals, shorten the key update cycle, and reduce the authentication threshold to 0.6;

[0118] Authentication process: The terminal initiates authentication, and each module works together. Assume that the authentication parameter of a high-risk terminal is 0.58;

[0119] Risk response and recording: The risk assessment module issues an alert and takes additional security measures;

[0120] The following is a table of authentication data for high-risk terminals:

[0121] Terminal Number Authentication parameters Certification results risk assessment 51 0.58 fail High risk 52 0.62 success Medium risk ... ... ... ...

[0122] The accuracy of high-risk terminal authentication has been increased to 90%.

[0123] Biometric Authentication:

[0124] Implementation environment: Equipped with high-precision biometric collection equipment;

[0125] Data preparation: Collect fingerprint and iris information of 80 end users, and set the matching accuracy threshold to 98%;

[0126] Authentication process: The user provides biometrics, and the biometric recognition module verifies it. Assume that the fingerprint matching accuracy of a certain user is 99%;

[0127] Effect evaluation: The success rate of biometric authentication reached 95%;

[0128] The following is a data table for biometric authentication:

[0129]

[0130] Edge Computing Assisted Certification:

[0131] Implementation environment: Deploy edge computing nodes near the terminal;

[0132] Data preparation: 120 terminals were selected for testing, and data before and after edge computing was involved was recorded;

[0133] Authentication process: The terminal sends a request, and the edge computing node pre-processes it. Assume that the response time of a terminal is shortened from 4 seconds to 1.5 seconds with the assistance of edge computing;

[0134] The following is a performance comparison table for edge computing assisted certification:

[0135]

[0136] Reduced average response time by 60%.

[0137] Dynamic adjustment of authentication policy:

[0138] Implementation environment: Establish a real-time monitoring system and data analysis platform;

[0139] Data preparation: Collect 2,000 authentication data from the past month;

[0140] Strategy adjustment process: Dynamically adjust the authentication strategy based on real-time data. Assume that the authentication success rate increases from 80% to 90% after adjustment.

[0141] The following is a comparison table of the effects before and after the authentication strategy adjustment:

[0142] Adjustment Phase Certification success rate Average response time Before adjustment 80％ 2.5 seconds After adjustment 90％ 2 seconds

[0143] Authentication performance has been significantly improved.

[0144] Through the above specific embodiments, the effective application of the cross-domain mutual trust identification authentication platform of the power terminal and multi-business system of the present invention in different scenarios is demonstrated. Actual data support and comparative tests show that the platform can provide reliable authentication services to ensure the safe and stable operation of the power system. In future applications, the platform functions will be continuously optimized and improved to adapt to the ever-changing power business needs.

[0145] In the formula In the , the update factor Update_Factor is a key factor. It is usually calculated based on multiple factors, which may include the time interval of system operation, the frequency of key use, changes in security policies, etc. For example, it can increase a fixed value every certain period of time according to a preset time period; or gradually increase according to the increase in the number of key uses. Its role is to control the rhythm and timing of key updates to ensure that the system key achieves a balance between security and computing resource consumption;

[0146] For the formula:

[0147] Risk_Assessment = ML(ID terminal , Historical_Data, Current_Behavior)

[0148] The machine learning algorithm ML in this paper uses a neural network algorithm based on deep learning. The neural network is trained through a large amount of historical data, including the past authentication status of different terminal identifiers, various types of historical behavior data, and known risk event records. During the training process, the terminal identifier is used as a feature to distinguish different terminals, the historical data is used to learn normal and abnormal patterns, and the current behavior is used as real-time input for real-time evaluation. The algorithm will output a quantitative risk assessment value based on the characteristics and patterns of these input data, reflecting the potential risk level in the current authentication process;

[0149] In the formula:

[0150] Authentication_Parameter=f(ID terminal ,Key system , Timestamp, AI_Feature), the authentication function f is a complex function that takes multiple factors into consideration. For example, the weight of the terminal identification may be relatively low, mainly used to identify the terminal identity; the weight of the system key is high to ensure the security of the authentication; the weight of the timestamp is moderate to prevent replay attacks; the weight of the terminal behavior feature is dynamically adjusted according to its impact on the authentication result. Assuming a simple calculation example, the authentication parameter can be the result of the weighted sum of each factor, such as:

[0151] Authentication_Parameter=01×ID terminal +0.5×Key system +0.2×Timestamp+0.2×Feature, in this example, the terminal ID terminal The weight is 0.1, the system key Key system The weight of is 0.5, the weight of timestamp is 0.2, and the weight of terminal behavior feature AI_Feature is 0.2.

[0152] The working principle of this cross-domain mutual trust identification authentication platform for power terminals and multi-business systems:

[0153] When the power terminal needs to interact with the multi-service system, it first sends an authentication request to the authentication request receiving module. The request contains basic information of the terminal, such as the terminal identification, etc. After receiving the request, the authentication request receiving module synchronously passes it to the identification generation module and the authentication processing module. The identification generation module then starts working according to the formula Unique_ID = Hash (ID terminal ‖Salt‖Prev_Hash, the terminal identification ID terminal Combined with the random salt value Salt, processed by the hash function Hash, and then connected to the hash value Prev_Hash of a block, a unique and difficult-to-forge identifier Unique_ID is generated. This identifier not only clarifies the identity of the terminal, but also provides a key basis for subsequent authentication;

[0154] At the same time, the authentication processing module starts to operate. It obtains the system key Key from the key management module system , receiving the terminal behavior feature AI_Feature that is initially processed and extracted from the edge computing module, combined with the current timestamp Timestamp and the terminal identification ID terminal , using the formula

[0155] Authentication_Parameter=f(ID terminal ,Key system , Timestamp, AI_Feature), the authentication parameter Authentication_Parameter is calculated through the preset authentication function f, where the introduction of Timestamp effectively prevents replay attacks and ensures the real-time and freshness of each authentication request; the integration of terminal behavior feature AI_Feature makes the authentication consideration more comprehensive and accurate, and can reflect the real-time status and behavior pattern of the terminal;

[0156] Next, the authentication result determination module takes over the authentication parameters calculated by the authentication processing module.

[0157] When Authentication_Parameter>Threshold, authentication is successful;

[0158] When Authentication_Parameter<=Threshold, authentication fails;

[0159] Compare the authentication parameters with the threshold value preset and adjusted by the authentication policy configuration module. If the authentication parameters are greater than the threshold value, the authentication is considered successful; otherwise, the authentication is considered failed. This threshold value is not fixed, but is flexibly set and dynamically adjusted by the authentication policy configuration module based on system security requirements, business importance, and terminal risk level.

[0160] In the entire certification process, the risk assessment module plays an important role. Based on the formula Risk_Assessment = ML (ID terminal , Historical_Data, Current_Behavior), using machine learning algorithm ML, comprehensive terminal identification ID terminal , historical data Historical_Data and current terminal behavior Current_Behavior, to conduct real-time assessment of potential risks in the authentication process. By learning and analyzing a large amount of historical data, it can keenly identify abnormal patterns or potential security threats, and promptly feed back the assessment results to the authentication policy configuration module and terminal information management module so that corresponding measures can be taken to reduce risks;

[0161] The biometric recognition module, when biometric authentication is required, when the end user provides biometric information, such as fingerprints, irises, etc., it is matched and verified with pre-stored templates;

[0162] The edge computing module is located near the terminal, and quickly performs preliminary processing and feature extraction on the data sent by the terminal, reducing data transmission volume and delay, improving authentication efficiency and real-time performance, and timely passing the extracted terminal behavior features to the authentication processing module and risk assessment module;

[0163] The key management module follows:

[0164] Using quantum encryption technology Quantum_Encrypt, according to the system key Key system Update the system key regularly with the update factor Update_Factor to ensure the security and timeliness of the key;

[0165] The logging module records the key steps and data of the authentication process in detail;

[0166] The terminal information management module is fully responsible for the storage, update and management of terminal information, and works in coordination with other modules;

[0167] The authentication policy configuration module dynamically adjusts the authentication policy according to the requirements of multiple business systems, changes in terminal security levels, and risk assessment results;

[0168] The anomaly detection module monitors the data of each module at all times. Once an anomaly is found, it immediately issues an alarm and transmits relevant information so that countermeasures can be taken;

[0169] In summary, the various modules of the platform work closely together and cooperate with each other to form a strict and efficient authentication system, providing solid protection for the safe and reliable interaction between power terminals and multi-business systems.

[0170] Example 3

[0171] This embodiment also provides a computer device, which is applicable to a cross-domain mutual trust identification authentication platform method between a power terminal and a multi-business system, and includes 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 a forced oscillation detection and positioning method for a distribution network as proposed in the above embodiment.

[0172] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, a forced oscillation detection and positioning method for a distribution network is implemented as proposed in the above embodiment.

[0173] 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 via a system bus. 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 covering 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.

[0174] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0175] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0176] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0177] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0178] 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 cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems, characterized by: include, Authentication request receiving module, identification generation module, authentication processing module, authentication result determination module, risk assessment module, biometric identification module, edge computing module, key management module, logging module, terminal information management module, authentication policy configuration module and anomaly detection module; The authentication request receiving module is used to receive the authentication request of the power terminal and pass the request to the identification generating module and the authentication processing module; The identification generation module is used to generate a unique identification based on the terminal identification, the random salt value and the hash value of the previous block; The authentication processing module is used to calculate authentication parameters based on the system key, the current timestamp and the terminal behavior characteristics.

2. The cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems according to claim 1 is characterized in that: The authentication result determination module compares the authentication parameters with the preset threshold to determine the authentication result; the risk assessment module assesses the authentication risk through a machine learning algorithm; the biometric feature recognition module is used to verify the biometric feature; The edge computing module is used to perform preliminary processing on the terminal behavior characteristics.

3. The cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems according to claim 2 is characterized in that: The key management module uses quantum encryption technology to regularly update the system key according to the system key and the update factor; the log recording module records the authentication process data; the terminal information management module stores and manages the terminal information; the authentication policy configuration module dynamically adjusts the authentication policy according to the risk assessment results.

4. The cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems according to claim 3 is characterized by: The anomaly detection module uses a deep learning algorithm to detect abnormal behavior based on historical anomaly data and real-time authentication process data.

5. The cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems according to claim 4 is characterized in that: When the authentication parameter is greater than the preset threshold, the authentication is determined to be successful; when the authentication parameter is less than or equal to the preset threshold, the authentication is determined to be failed.

6. The cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems according to claim 5 is characterized in that: The preliminary processing results of the edge computing module are fed back to the authentication processing module and the risk assessment module in real time.

7. The cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems according to claim 6 is characterized by: The authentication parameters calculated by the authentication processing module are sent to the authentication result determination module, and the authentication result determination module feeds back the result to the authentication request receiving module. At the same time, the risk assessment module obtains data from the authentication processing module for assessment and transmits the assessment result to the authentication policy configuration module.

8. The cross-domain mutual trust identification authentication platform method for power terminals and multi-business systems according to claim 7 is characterized by: The biometric identification module sends the identification result to the authentication processing module. After the edge computing module preliminarily processes the data, it passes the terminal behavior characteristics to the authentication processing module and the risk assessment module.

9. The cross-domain mutual trust identification authentication platform method of the power terminal and the multi-business system as claimed in claim 8, characterized in that: The terminal information management module performs information interaction with the authentication processing module and the authentication result determination module to store and manage terminal information.

10. The cross-domain mutual trust identification authentication platform method of the power terminal and the multi-business system according to claim 9, characterized in that: The authentication strategy configuration module adjusts the strategy according to the results of the risk assessment module, the requirements of the multi-business system and the changes in the security level of the power terminal, and passes the strategy to the relevant modules. The anomaly detection module obtains data from each module for detection and feeds back the results to the relevant modules.

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