Dual access mechanism implementation method and platform, computer equipment and storage medium

Abstract

The invention discloses a dual access mechanism implementation method and platform, computer equipment and a storage medium. The method comprises the following steps: firstly, generating initial black and white lists by using an automatic configuration tool and an intelligent recommendation system; after the gateway service receives the request, extracting request source information; the request source information is sent to a data analysis module for security check; matching the request information with a black list and a white list which are updated in real time; dynamically updating black and white lists by continuously monitoring network traffic and security events; and adjusting a data structure, a caching strategy and a load balancing strategy according to a performance monitoring result. The platform provided by the invention further comprises a powerful log and auditing system, data encryption and compliance are ensured, a cloud native architecture is supported, automatic deployment and horizontal extension are realized, and common security threats are effectively prevented. And the security can be effectively managed in a complex and high-concurrency network environment.

Description

Technical Field

[0001] The present invention relates to the field of gateway service technology, and in particular to a dual access mechanism implementation method, platform, computer equipment and storage medium. Background Art

[0002] In the field of gateway services, it is necessary to determine whether the request is allowed to be released based on the call source. At this time, the source access control (black and white list control) function can be used. Source access control restricts whether resources are passed based on the request source of the resource. If a whitelist is configured, only requests from the source in the whitelist can be passed; if a blacklist is configured, requests from the source in the blacklist will not be passed, and the rest of the requests will be passed.

[0003] As Internet applications become more complex and security requirements increase, traditional blacklist and whitelist configuration methods are unable to meet the needs of modern applications:

[0004] 1. Complex configuration: Detailed blacklists and whitelists need to be written in advance, and the configuration process is cumbersome and error-prone.

[0005] 2. Performance bottleneck: Frequent comparison operations will significantly reduce system performance, especially in high-concurrency scenarios.

[0006] 3. Lack of flexibility: Insufficient support for complex IP matching rules makes it difficult to fine-tune security policies. Summary of the invention

[0007] The purpose of the present invention is to provide a dual access mechanism implementation method, platform, computer device and storage medium, which can effectively manage security in a complex and highly concurrent network environment by introducing automated configuration tools and intelligent recommendation systems to solve the problems raised by the above-mentioned background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] The dual admission mechanism implementation method includes the following steps:

[0010] S1: Generates the initial blacklist and whitelist based on historical data and security policies by using automated configuration tools and intelligent recommendation systems;

[0011] S2: After receiving the request, the gateway service extracts the request source information;

[0012] S3: Send the request source information to the data analysis module for security check;

[0013] S4: Match the request information with the blacklist and whitelist updated in real time;

[0014] S5: Continuously monitor network traffic and security events, identify new threat patterns, and dynamically update blacklists and whitelists based on real-time data analysis and predictions from machine learning models;

[0015] S6: Monitor system performance and adjust data structure, cache strategy and load balancing strategy based on performance monitoring results.

[0016] Furthermore, the security check in S3 uses predefined data models and machine learning algorithms through the data analysis module to evaluate the legitimacy and security of the request.

[0017] Furthermore, the automated configuration tools in S1 include:

[0018] Configuration file parsing: The configuration file contains the initial settings and rules of the blacklist and whitelist;

[0019] Apply preset configuration templates: Templates are based on common security policies and business requirements;

[0020] User interface interaction: users can add, delete or modify blacklist and whitelist entries;

[0021] Verification and testing: Before applying a new configuration, verify the syntax and logic to ensure the correctness of the configuration;

[0022] Version control integration: record configuration changes in a version control system;

[0023] Deployment and monitoring: When the configuration is verified and tested, the tool automatically deploys the configuration to the gateway service.

[0024] Furthermore, the intelligent recommendation system in S1 includes:

[0025] Data collection: Collect data from various sources, including network traffic logs, user behavior data, and security incident reports;

[0026] Data processing: Processing the collected data, including removing irrelevant or redundant information, conversion and normalization;

[0027] Model training: Extract useful features from the processed data, use the features to train the machine learning model, and learn how to identify potential threats or security requests from the features;

[0028] Recommendation generation: Use the trained model to analyze real-time data and generate recommended changes to the blacklist and whitelist;

[0029] Feedback loop: compare recommendations with actual security incidents to assess the quality of recommendations.

[0030] Furthermore, when S4 matches the request information with the real-time updated blacklist and whitelist, it includes the following processing mechanisms:

[0031] Fast data structure: Use Trie tree or hash table data structure to store black and white lists to speed up search;

[0032] Caching mechanism: Use caching for frequently accessed IP addresses or request patterns to reduce repeated database queries and processing time;

[0033] Parallel processing: Implement parallel processing on multi-core processors to process multiple requests simultaneously to improve system throughput;

[0034] Load balancing: Implement load balancing in a distributed system to ensure that requests are evenly distributed.

[0035] The present invention also provides a technical solution: a platform for implementing a dual access mechanism, comprising a gateway service interface, an automated configuration tool, an intelligent recommendation system, a data analysis module, a data model library, a log and audit system, a user authority management module, an API and an integrated service module, wherein the gateway service interface is responsible for receiving and forwarding client requests to internal services, the data model library is used to store basic data of network security rules and algorithms, the log and audit system is used to record detailed information of all requests and security events, and the API and integrated service module are used to provide a RESTful API to allow other systems and services to be integrated with the DSAC platform.

[0036] Preferably, the platform adopts a cloud-native architecture and supports automated deployment and continuous integration / continuous deployment processes.

[0037] Preferably, all sensitive data on the platform is encrypted during transmission and storage, and supports common compliance standards.

[0038] The present invention provides another technical solution: a computer device for running a dual admission mechanism implementation method, comprising:

[0039] Processors, which handle large amounts of network requests and data;

[0040] At least 4GB of random access memory RAM to support complex data processing and multitasking operations;

[0041] Network interface, used to implement real-time monitoring and process network requests;

[0042] At least 100GB of internal storage space for storing logs, configuration files, and blacklist and whitelist data;

[0043] An operating system that supports running data encryption and compliance support software;

[0044] Disaster recovery module, including data backup and recovery functions, is used to protect data from hardware failure or data loss.

[0045] The present invention also provides another technical solution: a computer storage medium, used in a computer device, wherein the storage medium is a computer program for running a method for implementing a dual admission mechanism.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. The dual access mechanism implementation method, platform, computer device and storage medium of the present invention simplify the configuration process by automatically generating the initial black and white lists; after the gateway service receives the request, it extracts the relevant information and performs a security check; through data structure optimization and caching mechanism, efficient matching is ensured, and the black and white lists are updated in real time using machine learning models, thereby improving the flexibility and response speed of the system.

[0048] 2. The dual access mechanism implementation method, platform, computer device and storage medium of the present invention provide a platform including a powerful log and audit system to ensure data encryption and compliance, support cloud-native architecture, realize automated deployment and horizontal expansion, effectively prevent common security threats, and enhance the stability and security of the system.

[0049] 3. The dual access mechanism implementation method, platform, computer device and storage medium of the present invention can effectively manage security in complex and highly concurrent network environments by introducing automated configuration tools and intelligent recommendation systems. It not only simplifies the configuration, but also greatly improves the performance and security of the system, and adapts to the needs of modern complex network environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 The present invention is a flowchart of the method for implementing the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] See also Figure 1 The dual admission mechanism implementation method provided by the embodiment of the present invention comprises the following steps:

[0053] S1: Generate an initial blacklist and whitelist based on historical data and security policies by using automated configuration tools and intelligent recommendation systems. The automated configuration tools include:

[0054] Configuration file parsing: The configuration file contains the initial settings and rules of the blacklist and whitelist. Specifically, the configuration file is usually stored in JSON, YAML, or XML format, which defines server information, blacklist and whitelist entries, and other security settings.

[0055] Apply preset configuration templates: Templates are based on common security policies and business requirements; users can select a template and customize it according to their actual situation, and the tool will automatically fill in the variables in the template to generate the configuration;

[0056] User interface interaction: Users can add, delete or modify blacklist and whitelist entries; the GUI provides forms and lists to allow users to easily manage configurations and provide immediate feedback;

[0057] Verification and testing: Before applying a new configuration, verify the syntax and logic to ensure the correctness of the configuration; you can also simulate requests to test the validity of the configuration to ensure that the new settings do not accidentally block legitimate traffic or allow malicious traffic;

[0058] Version control integration: Record configuration changes in a version control system, such as Git, to track change history and roll back to previous configurations, to quickly restore services when configuration issues occur, and to ensure configuration consistency and traceability;

[0059] Deployment and monitoring: When the configuration is verified and tested, the tool will automatically deploy the configuration to the gateway service and monitor the effect of the configuration, such as the request pass and rejection rates, and the system response time.

[0060] In the above steps, the intelligent recommendation system includes:

[0061] Data collection: Collect data from various sources, including network traffic logs, user behavior data, and security incident reports. Data collection is done in real time to ensure that the recommendation system can respond to the latest network activities.

[0062] Data processing: Processing the collected data, including removing irrelevant or redundant information, conversion and normalization, to facilitate subsequent machine learning model processing;

[0063] Model training: Extract useful features from the processed data, use the features to train the machine learning model, and learn how to identify potential threats or security requests from the features;

[0064] Recommendation generation: Use the trained model to analyze real-time data and generate recommended changes to blacklists and whitelists. These recommendations are based on the model's predictions, such as whether a certain IP address is likely to be a source of attack.

[0065] Feedback loop: compare the recommendation results with actual security incidents to evaluate the quality of the recommendations, and the feedback will be used to adjust and optimize the model to improve its accuracy and efficiency.

[0066] S2: After receiving the request, the gateway service extracts the request source information, including IP address, user agent, etc.

[0067] S3: Send the request source information to the data analysis module for security check; the security check uses the predefined data model and machine learning algorithm through the data analysis module to evaluate the legitimacy and security of the request;

[0068] S4: Match the request information with the real-time updated blacklist and whitelist; if the request source is in the whitelist, the request is released; if it is in the blacklist, the request is rejected; when matching, the following processing mechanisms are included:

[0069] Fast data structure: Use data structures such as Trie trees or hash tables to store black and white lists to speed up search;

[0070] Caching mechanism: Use cache for frequently accessed IP addresses or request patterns to reduce repeated database queries and processing time;

[0071] Parallel processing: Implement parallel processing on multi-core processors to process multiple requests simultaneously and improve system throughput;

[0072] Load balancing: Implement load balancing in a distributed system to ensure even distribution of requests and avoid single point overload.

[0073] S5: Continuously monitor network traffic and security events, identify new threat patterns, and dynamically update blacklists and whitelists based on real-time data analysis and predictions from machine learning models;

[0074] S6: Monitor system performance and adjust data structure, cache strategy, and load balancing strategy based on performance monitoring results to ensure that matching and updating operations of blacklists and whitelists do not become performance bottlenecks.

[0075] Based on the above-mentioned dual access mechanism implementation method, the present invention also provides a platform for the dual access mechanism implementation method, including a gateway service interface, an automated configuration tool, an intelligent recommendation system, a data analysis module, a data model library, a log and audit system, a user authority management module, an API and an integrated service module, wherein the gateway service interface is responsible for receiving and forwarding client requests to internal services, realizing the functions of request interception, identity authentication and authorization, and the data model library is used to store basic data of network security rules and algorithms, and supports the integration of multiple data sources, such as IP reputation libraries, threat intelligence feeds, etc. The log and audit system is used to record detailed information of all requests and security events, thereby providing audit and reporting functions to facilitate security analysis and compliance checks. The API and integrated service modules provide a RESTful API, allowing other systems and services to be integrated with the DSAC platform, and support integration with existing security information and event management (SIEM) systems, intrusion detection systems (IDS), etc.

[0076] The above platform adopts cloud-native architecture and supports automated deployment and continuous integration / continuous deployment (CI / CD) processes, which enables rapid horizontal expansion to meet demand when load changes. Automated deployment allows frequent deployment of code changes to the production environment, making it easier to iterate and deploy new features.

[0077] All sensitive data on the above platforms are encrypted during transmission and storage, and support common compliance standards. Data encryption technology can protect the confidentiality of data and prevent unauthorized personnel from obtaining the true content of the data. Encryption algorithms can convert data into a difficult-to-identify form to prevent the risk of leakage during data transmission and storage. Compliance standards include GDPR, HIPAA, etc.

[0078] In order to further better explain the above embodiment, the present invention also provides a computer device for running a dual admission mechanism implementation method, wherein the computer device is configured with:

[0079] Processors, which handle large amounts of network requests and data;

[0080] At least 4GB of random access memory RAM to support complex data processing and multitasking operations;

[0081] Network interface, used to implement real-time monitoring and process network requests;

[0082] At least 100GB of internal storage space for storing logs, configuration files, and blacklist and whitelist data;

[0083] An operating system that supports running data encryption and compliance support software;

[0084] Disaster recovery module, including data backup and recovery functions, is used to protect data from hardware failure or data loss.

[0085] Based on this, the present invention also provides a computer storage medium, which is used in the above-mentioned computer device, wherein the storage medium is a computer program for running the dual access mechanism implementation method.

[0086] In summary: the dual access mechanism implementation method, platform, computer equipment and storage medium provided by the present invention can effectively manage security in a complex and highly concurrent network environment by introducing automated configuration tools and intelligent recommendation systems. First, the method automatically generates an initial black and white list, simplifying the configuration process; after the gateway service receives the request, it extracts relevant information and performs a security check; through data structure optimization and caching mechanisms, efficient matching is ensured, and the black and white lists are updated in real time using machine learning models, which improves the flexibility and response speed of the system. The platform also includes a powerful log and audit system to ensure data encryption and compliance, support cloud-native architecture, realize automated deployment and horizontal expansion, effectively prevent common security threats, and enhance the stability and security of the system. This comprehensive approach not only simplifies the configuration, but also greatly improves the performance and security of the system, and adapts to the needs of modern complex network environments.

[0087] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for implementing a dual admission mechanism, characterized in that: The following steps are involved: S1: Generates the initial blacklist and whitelist based on historical data and security policies by using automated configuration tools and intelligent recommendation systems; S2: After receiving the request, the gateway service extracts the request source information; S3: Send the request source information to the data analysis module for security check; S4: Match the request information with the blacklist and whitelist updated in real time; S5: Continuously monitor network traffic and security events, identify new threat patterns, and dynamically update blacklists and whitelists based on real-time data analysis and predictions from machine learning models; S6: Monitor system performance and adjust data structure, cache strategy and load balancing strategy based on performance monitoring results.

2. The method for implementing the dual admission mechanism as claimed in claim 1, characterized in that: Security checks in S3 use predefined data models and machine learning algorithms through the data analysis module to evaluate the legitimacy and security of requests.

3. The method for implementing the dual admission mechanism as claimed in claim 1, characterized in that: The automated configuration tools in S1 include: Configuration file parsing: The configuration file contains the initial settings and rules of the blacklist and whitelist; Apply preset configuration templates: Templates are based on common security policies and business requirements; User interface interaction: users can add, delete or modify blacklist and whitelist entries; Verification and testing: Before applying a new configuration, verify the syntax and logic to ensure the correctness of the configuration; Version control integration: record configuration changes in a version control system; Deployment and monitoring: When the configuration is verified and tested, the tool automatically deploys the configuration to the gateway service.

4. The method for implementing the dual admission mechanism according to claim 1, characterized in that: The intelligent recommendation system in S1 includes: Data collection: Collect data from various sources, including network traffic logs, user behavior data, and security incident reports; Data processing: Processing the collected data, including removing irrelevant or redundant information, conversion and normalization; Model training: Extract useful features from the processed data, use the features to train the machine learning model, and learn how to identify potential threats or security requests from the features; Recommendation generation: Use the trained model to analyze real-time data and generate recommended changes to the blacklist and whitelist; Feedback loop: compare recommendations with actual security incidents to assess the quality of recommendations.

5. The method for implementing the dual admission mechanism as claimed in claim 1, characterized in that: When S4 matches the request information with the real-time updated blacklist and whitelist, it includes the following processing mechanisms: Fast data structure: Use Trie tree or hash table data structure to store black and white lists to speed up search; Caching mechanism: Use caching for frequently accessed IP addresses or request patterns to reduce repeated database queries and processing time; Parallel processing: Implement parallel processing on multi-core processors to process multiple requests simultaneously to improve system throughput; Load balancing: Implement load balancing in a distributed system to ensure that requests are evenly distributed.

6. A platform for implementing a dual admission mechanism, characterized in that: It includes a gateway service interface, an automated configuration tool, an intelligent recommendation system, a data analysis module, a data model library, a log and audit system, a user rights management module, an API and an integrated service module. The gateway service interface is responsible for receiving and forwarding client requests to internal services. The data model library is used to store basic data of network security rules and algorithms. The log and audit system is used to record detailed information of all requests and security events. The API and integrated service module is used to provide a RESTful API to allow other systems and services to be integrated with the DSAC platform.

7. The platform for implementing the dual admission mechanism method according to claim 6, characterized in that: The platform adopts a cloud-native architecture and supports automated deployment and continuous integration / continuous deployment processes.

8. The platform for implementing the dual admission mechanism as claimed in claim 6, characterized in that: The platform encrypts all sensitive data during transmission and storage and supports common compliance standards.

9. A computer device, used to run the dual access mechanism implementation method according to any one of claims 1 to 5, characterized in that: include: Processors, which handle large amounts of network requests and data; At least 4GB of random access memory RAM to support complex data processing and multitasking operations; Network interface, used to implement real-time monitoring and process network requests; At least 100GB of internal storage space for storing logs, configuration files, and blacklist and whitelist data; An operating system that supports running data encryption and compliance support software; Disaster recovery module, including data backup and recovery functions, is used to protect data from hardware failure or data loss.

10. A computer storage medium, used in a computer device as claimed in claim 9, characterized in that: The storage medium is a computer program for running a method for implementing a dual admission mechanism.

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