A link adaptive encryption and intelligent operation and maintenance decision system and method for communication automation

Abstract

The application belongs to the technical field of communication automation, and discloses a link adaptive encryption and intelligent operation and maintenance decision system and method for communication automation. The application covers the whole process of communication automation from link control, data security to operation and maintenance decision by constructing three core modules of link adaptive adjustment, data transmission encryption and intelligent operation and maintenance decision. The application breaks through the industry bottleneck of traditional communication automation, such as passive link adjustment, rigid data encryption and lag operation and maintenance decision, realizes adaptive adaptation of link state, dynamic encryption of data transmission and precise and efficient operation and maintenance decision, significantly improves the link stability, data security and intelligent level of operation and maintenance of communication automation, and adapts to the needs of industrial communication, public communication, private network communication and other scenes, especially solves the technical problems of link adaptation imbalance, inefficient data encryption and blind operation and maintenance decision.

Description

Technical Field

[0001] This invention belongs to the field of information technology, specifically relating to a communication automation link adaptive encryption and intelligent operation and maintenance decision-making system and method. Background Technology

[0002] In the current field of communication automation, with the deep application of technologies such as the Industrial Internet and 5G private networks, communication scenarios are characterized by "diversified transmission, highly sensitive data, and complex operation and maintenance." This places increasingly higher demands on link adaptability, data security protection, and operational decision-making efficiency. However, existing technologies still face specific and unresolved practical problems in the three sub-scenarios of "link adjustment, data encryption, and operational decision-making." These are all scenario-specific problems, not macro-level challenges, and have no overlap with the current technical direction outlined in this document. Specifically: 1. Passive link adjustment without dynamic identification and adaptation: Existing communication link adjustment mostly adopts the "fixed parameters + manual intervention" mode, lacking dynamic identification of link status and no adaptive adjustment mechanism for link parameters; this results in link parameters being unable to dynamically adapt to link status and service requirements, easily leading to problems such as link congestion, transmission interruption, and weak interference resistance, and failing to meet the link requirements of high-standard communication scenarios such as industrial-grade and private networks.

[0003] 2. Rigid data encryption, lacking dynamic keys and hierarchical encryption: Existing data transmission encryption mostly adopts the "fixed key + unified encryption" model, lacking dynamic generation of data encryption keys and a hierarchical encryption mechanism; this makes the keys easy to crack, encryption efficiency low, and unable to dynamically adjust the encryption strategy according to the data security level and transmission scenario, making it difficult to meet the secure transmission requirements of highly sensitive data (such as industrial secrets and government data), and posing a risk of data leakage.

[0004] 3. Delayed operation and maintenance decision-making, lack of anomaly diagnosis and intelligent decision-making: Current communication operation and maintenance mostly adopts the "manual inspection + post-event handling" model, which lacks accurate diagnosis of operation and maintenance anomalies and has no intelligent mechanism for generating operation and maintenance decisions. This results in the inability to identify and accurately locate operation and maintenance anomalies in a timely manner, and operation and maintenance solutions rely on human experience, leading to low decision-making efficiency, poor adaptability, and problems such as high operation and maintenance costs and increased communication interruption time, which does not meet the needs of automated and intelligent operation and maintenance of communication.

[0005] Existing communication automation methods have not achieved core innovations in "link adaptive adjustment, data transmission encryption, and intelligent operation and maintenance decision-making," especially in link state modeling, encryption key solving, and operation and maintenance decision modeling, which have significant gaps and cannot solve the above-mentioned specific problems. Summary of the Invention

[0006] In response to the three specific problems raised in the background art, the purpose of this invention is to provide a link adaptive encryption and intelligent operation and maintenance decision system and method for communication automation.

[0007] The present invention is implemented through the following specific technical solution: (a) Link Adaptive Adjustment Module The core of this module is to accurately identify link status, dynamically adapt parameters, and suppress interference. It constructs a link adaptive adjustment modeling system to solve the problems of passive link adjustment, link congestion, and weak interference resistance. It improves the stability and adaptability of communication links, provides link support for efficient automated transmission, and meets the development needs of strategic emerging industries such as the Industrial Internet and new mobile communication networks.

[0008] Modeling Approach: Abandoning the traditional extensive modeling approach of "fixed parameters and manual intervention," we construct an integrated modeling logic of "link data acquisition - link feature modeling - link status identification modeling - parameter adjustment modeling - interference suppression modeling - verification and optimization modeling." Combining link status characteristics (bandwidth utilization, transmission rate, bit error rate), service transmission requirement characteristics (transmission rate requirements, latency requirements, reliability requirements), and interference characteristics (interference type, interference intensity, interference frequency), we establish link feature models, link status identification models, link parameter adjustment models, interference suppression models, and verification and optimization models. We design dynamic link status identification and adaptive link parameter adjustment to achieve adaptive link adjustment.

[0009] First, a link monitoring component is deployed to collect communication link status data (bandwidth utilization, transmission rate, bit error rate), service transmission requirement data (transmission rate requirements, latency requirements), and interference data (interference type, interference intensity), constructing a link adaptive adjustment data resource pool. Then, a dynamic link status identification system is designed to extract the core features of link status, interference, and service requirements, building a link status identification model to achieve accurate link status identification, anomaly prediction, and type classification, accurately capturing abnormal states such as link congestion and interference. Next, an adaptive adjustment model for link parameters is designed. Based on the link status identification results and service transmission requirements, a link parameter adjustment model is built to dynamically adjust link bandwidth, encoding method, and transmission rate, achieving link adaptive adaptation and interference suppression, avoiding link congestion and transmission interruptions. Finally, a verification and optimization model is built to quantify link stability, transmission efficiency, and interference suppression effects, dynamically optimizing parameters and adjustment strategies to ensure the effectiveness of link adaptive adjustment.

[0010] 1: Dynamic identification of link status To address the issues of inaccurate link status identification and inability to predict anomalies in existing technologies, an integrated model is constructed that combines link features, interference features, and business requirements modeling. This model enables accurate identification of link status, anomaly prediction, and type classification, resolving the core pain point of passive link adjustment and filling the technological gap in dynamic link status identification for communication automation.

[0011] 2: Adaptive adjustment of link parameters To address the problem of "fixed link parameters and inability to dynamically adapt" in existing technologies, an integrated model of link status, service requirements, and parameter adjustment is constructed to achieve dynamic adjustment of link parameters and interference suppression, solve the problems of link congestion and weak interference resistance, and fill the technical gap in adaptive adjustment of link parameters in communication automation.

[0012] (ii) Data transmission encryption module This module's core functionality includes dynamic generation of encryption keys, hierarchical encryption of data, and secure transmission. It constructs a data transmission encryption modeling system to address issues such as rigid data encryption, easily cracked keys, and low encryption efficiency. This improves the security and transmission efficiency of communication data, providing security for highly sensitive data transmission in automated communication, and aligns with the development needs of network security and the strategic emerging industries of new mobile communication networks.

[0013] Modeling Approach: Abandoning the traditional extensive modeling approach of "fixed key, unified encryption," we construct an integrated modeling logic of "data feature collection - data security level modeling - key generation modeling - hierarchical encryption modeling - security verification modeling - verification optimization modeling." Combining communication data characteristics (data type, data size, sensitivity), security level characteristics (core secrets, general secrets, general data), and encryption requirement characteristics (encryption efficiency, security strength), we establish data feature models, data security level models, key generation models, hierarchical encryption models, security verification models, and verification optimization models. We design dynamic generation of data encryption keys and hierarchical encrypted data transmission to achieve encrypted data transmission.

[0014] First, deploy data acquisition and security monitoring components to collect communication data characteristics (data type, sensitivity), encryption requirement data (encryption efficiency, security strength), and security level data (core confidentiality, general confidentiality), and construct a data transmission encryption resource pool. Then, design a dynamic data encryption key generation system, extracting core features of data characteristics, timestamps, and security levels to build a key generation model. Combined with a key generation calculation formula, this system enables dynamic generation and security verification of encryption keys, ensuring key uniqueness, security, and timeliness, and preventing key cracking. Next, design a hierarchical data encryption transmission system. Based on data security levels and encryption requirements, construct a hierarchical data encryption model, employing differentiated encryption strategies for data of different security levels (high-strength encryption for core confidential data, and high-efficiency encryption for general data) to achieve secure and efficient data transmission. Finally, construct a verification and optimization model to quantify key security, encryption efficiency, and data transmission security, dynamically optimizing parameters and encryption strategies to ensure effective data transmission encryption.

[0015] 3: Dynamic generation of data encryption keys To address the issues of "fixed keys, susceptibility to cracking, and low security" in existing technologies, an integrated model is constructed that combines data features, timestamps, and security level modeling. Combined with key generation calculation formulas, this model enables dynamic generation and security verification of encryption keys, solving the problem of insufficient key security and filling the technological gap in dynamic generation of encryption keys for automated communication data.

[0016] 4: Data is transmitted with hierarchical encryption. To address the issues of "single encryption strategies and low encryption efficiency" in existing technologies, an integrated model of data security levels, encryption requirements, and hierarchical encryption is constructed to achieve differentiated encrypted transmission of data with different security levels. This solves the problems of rigid encryption and low efficiency, and fills the technological gap in hierarchical encrypted transmission of data in automated communication.

[0017] (III) Intelligent Decision-Making Module for Operation and Maintenance This module is designed to accurately diagnose operational anomalies, intelligently generate and execute operational solutions in a closed loop, and build an intelligent decision-making modeling system for operations and maintenance. It addresses issues such as delayed operational decisions, ambiguous anomaly localization, and low decision-making efficiency, thereby improving the intelligence level and efficiency of automated communication operations and maintenance, reducing operational costs, and meeting the development needs of strategic emerging industries such as the Industrial Internet and new mobile communication networks.

[0018] Modeling Approach: Abandoning the traditional extensive modeling approach of "manual inspection and post-event handling," we construct an integrated modeling logic encompassing "operation and maintenance data collection - equipment operation modeling - anomaly feature modeling - anomaly diagnosis modeling - decision generation modeling - closed-loop execution modeling - verification and optimization modeling." Combining equipment operation characteristics (operation parameters, wear level, fault records), link anomaly characteristics (anomaly type, anomaly degree, impact range), and operation and maintenance requirement characteristics (operation and maintenance cost, handling timeliness, recovery requirements), we establish equipment operation models, anomaly feature models, anomaly diagnosis models, decision generation models, closed-loop execution models, and verification and optimization models. We design precise diagnosis of operation and maintenance anomalies and intelligent generation of operation and maintenance decisions to achieve intelligent operation and maintenance decision-making.

[0019] First, deploy operation and maintenance monitoring and data acquisition components to collect communication equipment operation data (operation parameters, fault records), link anomaly data (anomaly type, impact scope), and operation and maintenance requirement data (handling timeliness, recovery requirements), thus constructing an intelligent operation and maintenance decision-making data resource pool. Then, design a precise diagnosis system for operation and maintenance anomalies, extracting core characteristics of equipment operation and link anomalies, and constructing an anomaly diagnosis model to achieve accurate location, type identification, and severity assessment of operation and maintenance anomalies, avoiding missed or false diagnoses. Next, design intelligent generation of operation and maintenance decisions, constructing a decision generation model based on anomaly diagnosis results and operation and maintenance requirements to intelligently generate suitable operation and maintenance solutions (including handling steps, resource allocation, and recovery time limits), achieving precise, efficient, and closed-loop execution of operation and maintenance decisions. Finally, construct a verification and optimization model to quantify anomaly diagnosis accuracy, decision adaptability, and operation and maintenance efficiency, dynamically optimizing parameters and decision-making strategies to ensure the effectiveness of intelligent operation and maintenance decisions.

[0020] 5: Precise diagnosis of operational anomalies To address the issues of inaccurate identification and ambiguous location of operational anomalies in existing technologies, an integrated model for equipment operation, link anomalies, and anomaly diagnosis is constructed. This model enables precise location, type identification, and severity assessment of operational anomalies, resolving the problem of lagging operational anomaly diagnosis and filling the technological gap in accurate diagnosis of operational anomalies in communication automation.

[0021] 6: Intelligent generation of operation and maintenance decisions To address the problems of "manual reliance on operation and maintenance decisions, low efficiency, and poor adaptability" in existing technologies, an integrated model of anomaly diagnosis results, operation and maintenance requirements, and decision generation is constructed to realize the intelligent generation and closed-loop execution of operation and maintenance solutions, solve the problem of blind operation and maintenance decisions, and fill the technological gap in intelligent generation of communication automation operation and maintenance decisions.

[0022] Beneficial effects 1. Dynamic Link Status Identification: Abandoning the crude approach of fixed parameters, we construct an integrated system for modeling link features, interference features, and business requirements. This significantly improves the accuracy of link status identification and the timeliness of anomaly prediction, completely solving the problems of inaccurate link status identification and inability to predict anomalies. It focuses on innovation in precise link status management and control, meeting the development needs of strategic emerging industries such as the Industrial Internet and new mobile communication networks. 2. Adaptive Link Parameter Adjustment: Constructing an integrated system of link status, service requirements, and parameter adjustment, significantly improving link stability, transmission efficiency, and interference resistance, completely solving the problem of fixed link parameters and inability to dynamically adapt, and filling the technical gap in adaptive link parameter adjustment; 3. Dynamic generation of data encryption keys: Constructing an integrated system for modeling data features, timestamps, and security levels, significantly improving key security, uniqueness, and timeliness, completely solving the problems of fixed keys and easy cracking, focusing on data transmission security innovation, and meeting the development needs of strategic emerging industries in cybersecurity; 4. Data hierarchical encryption transmission: Construct an integrated system of data security levels, encryption requirements and hierarchical encryption, significantly improve encryption efficiency and data transmission security, completely solve the problems of single encryption strategy and low encryption efficiency, and fill the technical gap in data hierarchical encryption transmission; 5. Precise diagnosis of operation and maintenance anomalies: Construct an integrated system for equipment operation, link anomalies and anomaly diagnosis, significantly improving the accuracy of anomaly diagnosis and positioning accuracy, completely solving the problems of inaccurate identification and vague positioning of operation and maintenance anomalies, focusing on intelligent innovation in operation and maintenance, and meeting the development needs of strategic emerging industries in the industrial internet; 6. Intelligent Generation of Operation and Maintenance Decisions: Construct an integrated system for anomaly diagnosis results, operation and maintenance requirements, and decision generation, significantly improving the efficiency and adaptability of operation and maintenance decisions, completely solving the problem of reliance on manual operation and maintenance decisions and low efficiency, filling the technological gap in intelligent generation of operation and maintenance decisions, and meeting the requirements of the invention priority examination policy. Attached Figure Description

[0023] Figure 1 : Workflow diagram and detailed implementation of the link adaptive adjustment module The following four specific embodiments illustrate the implementation steps of the present invention in detail.

[0024] Example 1: Industrial-grade confidential data communication scenario Implementation steps Step 1: Data Acquisition and Parameter Setting: Collect link status data, service transmission requirement data, interference data, communication data characteristics (industrial confidential data, ordinary production data), encryption requirement data, and security level data for industrial-grade confidential data communication scenarios; and set the security entropy threshold for core confidential data keys. Ordinary confidential data Set the influence coefficient , , ( ).

[0025] Step 2: Link Adaptive Adjustment: By adopting dynamic link status identification and adaptive adjustment of link parameters, the characteristics of link status, interference and service requirements are extracted, a link status identification and parameter adjustment model is constructed, and link parameters are dynamically adjusted to suppress interference, so as to achieve link adaptive adaptation and ensure the stability and rate requirements of data transmission.

[0026] Step 3: Dynamic Generation of Data Encryption Keys: A dynamic data encryption key generation method is employed. This involves extracting data features, timestamps, and security level characteristics to construct a key generation model, and then using a key generation calculation formula. It generates dynamic encryption keys, performs security verification on the keys, ensures the uniqueness, security and timeliness of the keys, and prevents the keys from being cracked.

[0027] Step 4: Data Hierarchical Encryption Transmission: Data hierarchical encryption transmission is adopted. Based on the data security level, a data hierarchical encryption model is constructed. High-strength encryption strategy is used for industrial confidential data, and efficient encryption strategy is used for ordinary production data to achieve secure and efficient data transmission and prevent data leakage.

[0028] Step 5: Full-process verification and optimization: Verify link stability, transmission efficiency, key security, and encryption efficiency to ensure that they meet the requirements of industrial-grade confidential data communication scenarios; collect feedback data on link adjustment and data encryption, optimize parameters and adjustment, and encryption strategies to improve adaptability to industrial-grade confidential data communication scenarios.

[0029] Modeling Innovation Principles Abandoning the traditional, crude modeling approach of "fixed parameters, fixed keys, and unified encryption," this paper constructs an integrated closed-loop model of "link adjustment and data encryption." It uses the high stability and security requirements, link characteristics, data characteristics, and security levels of industrial-grade confidential data communication as core inputs, overcoming the limitations of passive link adjustment and rigid data encryption. Link adjustment modeling achieves dynamic adaptation of link parameters and interference suppression; key generation modeling achieves dynamic generation and security verification of encryption keys; and hierarchical encryption modeling achieves differentiated encryption of data at different security levels, filling the gap in integrated modeling of link adjustment and data encryption for industrial-grade confidential data communication. The modeling process focuses on the high stability and high security requirements of industrial-grade confidential data communication scenarios, completely different from the fixed parameter and fixed key modeling approaches and technical directions of existing technologies. It also has no overlap with the current modeling logic, representing a completely new modeling direction that aligns with the development needs of the industrial internet and cybersecurity strategic emerging industries, as well as the requirements of the invention priority examination policy.

[0030] Dynamic link status identification, through modeling link characteristics, interference characteristics, and business requirements, and employing dynamic identification strategies, significantly improves the accuracy of link status identification and the timeliness of anomaly prediction compared to the traditional fixed-parameter mode. This completely solves the problems of inaccurate link status identification and inability to predict anomalies, providing stable link support for industrial-grade confidential data transmission. Adaptive link parameter adjustment, through modeling link status, business requirements, and parameter adjustment, and employing dynamic adjustment strategies, significantly improves link stability, transmission efficiency, and interference resistance compared to the traditional fixed-parameter mode, completely solving the problems of link congestion and weak interference resistance. Dynamic data encryption key generation, through modeling data characteristics, timestamps, and security levels, and employing key generation calculation formulas, significantly improves the accuracy of link status identification and the timeliness of anomaly prediction compared to the traditional fixed-key mode. The key security, uniqueness, and timeliness are significantly improved, completely solving the problem of easy key cracking and providing core protection for secure data transmission. Data is transmitted with hierarchical encryption, which, through data security levels, encryption requirements, hierarchical encryption modeling, and differentiated encryption strategies, significantly improves encryption efficiency and data transmission security compared to traditional unified encryption modes, completely solving the problems of single encryption strategies and low encryption efficiency. These four synergistic effects enable industrial-grade confidential data communication to achieve "high stability and high security." Compared to existing technologies, link stability, data security, and transmission efficiency are qualitatively improved, fully meeting the high requirements of industrial-grade confidential data communication and conforming to the requirements of the invention priority examination policy of "enhancing core industrial competitiveness and ensuring network security."

[0031] Existing technologies employ a "fixed link parameters + fixed key + unified encryption" model, lacking dynamic link status identification, adaptive link parameter adjustment, dynamic data encryption key generation, and hierarchical encrypted data transmission. This passive link adjustment and rigid data encryption fail to meet the high stability and security requirements of industrial-grade confidential data communication, easily leading to link congestion and data leakage. This embodiment, through innovation and model optimization, achieves adaptive link adjustment and data transmission encryption for industrial-grade confidential data communication, completely resolving the pain points of existing technologies. Link stability, transmission efficiency, key security, and encryption efficiency all meet the standards for industrial-grade confidential data communication scenarios. Furthermore, it does not overlap with existing technologies, current technical directions, or modeling approaches, highlighting its innovation, strong practicality, and compliance with the development needs of strategic emerging industries and the requirements of invention priority examination policies.

[0032] Example 2: Intelligent Decision-Making Scenario for Public Communication Network Operation and Maintenance (corresponding to Link Adaptive Adjustment and Intelligent Decision-Making Module for Operation and Maintenance) Implementation steps Step 1: Relevant Data Collection: Deploy monitoring and data collection components to collect link status data, service transmission demand data, interference data, equipment operation data, link anomaly data, and operation and maintenance demand data in public communication network scenarios, and build a data resource pool for link adjustment and operation and maintenance decisions.

[0033] Step 2: Link Adaptive Adjustment: By adopting dynamic link status identification and adaptive adjustment of link parameters, the characteristics of link status, interference and service requirements are extracted, a link status identification and parameter adjustment model is constructed, and link parameters are dynamically adjusted to suppress interference, thereby achieving link adaptive adaptation and ensuring smooth transmission of public communication networks.

[0034] Step 3: Precise diagnosis of operation and maintenance anomalies: By adopting precise diagnosis of operation and maintenance anomalies, the core characteristics of equipment operation and link anomalies are extracted, and an anomaly diagnosis model is constructed to achieve accurate location, type identification and severity assessment of operation and maintenance anomalies (such as equipment failure and link interruption), avoiding missed or misjudged anomalies.

[0035] Step 4: Intelligent Generation of Operation and Maintenance Decisions: The intelligent generation of operation and maintenance decisions is adopted. Based on the anomaly diagnosis results and operation and maintenance requirements, a decision generation model is built to intelligently generate suitable operation and maintenance solutions (handling steps, resource allocation, recovery time limits), so as to achieve accurate, efficient and closed-loop execution of operation and maintenance decisions and reduce operation and maintenance costs.

[0036] Step 5: Continuous optimization: Verify link stability, transmission efficiency, anomaly diagnosis accuracy, and operational decision adaptability; collect scenario feedback data, optimize parameters and adjustments, and decision-making strategies to improve adaptability to public communication network scenarios and ensure stable network operation and efficient maintenance.

[0037] Modeling Innovation Principles Abandoning the traditional extensive modeling approach of "fixed link parameters, manual operation and maintenance, and post-event handling," this paper constructs an integrated closed-loop model of "link adjustment - anomaly diagnosis - operation and maintenance decision-making." It takes the high smoothness and high operation and maintenance efficiency requirements of public communication networks, link characteristics, equipment operating characteristics, and operation and maintenance needs as core inputs, overcoming the limitations of passive link adjustment and lagging operation and maintenance decision-making. Link adjustment modeling achieves dynamic adaptation of link parameters and interference suppression; anomaly diagnosis modeling achieves accurate location and identification of operation and maintenance anomalies; and decision generation modeling achieves intelligent generation and closed-loop execution of operation and maintenance solutions, filling the gap in integrated modeling of link adjustment and intelligent operation and maintenance decision-making in public communication networks. The modeling process focuses on the scenario requirements of multi-user, high smoothness, and high operation and maintenance efficiency in public communication networks. It is completely different from the fixed parameter and manual operation and maintenance modeling approaches and technical directions of existing technologies, and has no overlap with the current modeling logic. It represents a completely new modeling direction that meets the development needs of strategic emerging industries such as the Industrial Internet and new mobile communication networks.

[0038] Dynamic link status identification, through link characteristics, interference characteristics, and service requirements modeling and dynamic identification strategies, significantly improves the accuracy of link status identification and the timeliness of anomaly prediction compared to the traditional fixed parameter mode, completely solving the problems of inaccurate link status identification and inability to predict anomalies, ensuring smooth transmission in public communication networks; Adaptive link parameter adjustment, through link status, service requirements, and parameter adjustment modeling and dynamic adjustment strategies, significantly improves link stability, transmission efficiency, and interference resistance compared to the traditional fixed parameter mode, completely solving the problems of link congestion and weak interference resistance; Precise diagnosis of operation and maintenance anomalies, through equipment operation, link anomalies, and other anomalies... Diagnostic modeling and precise positioning strategies significantly improve the accuracy of anomaly diagnosis and positioning precision compared to traditional manual inspection methods, completely solving the problems of inaccurate identification and vague positioning of operational anomalies. Intelligent generation of operational decisions, through anomaly diagnosis results, operational needs, and decision generation modeling, and intelligent decision-making strategies, significantly improves the efficiency and adaptability of operational decisions compared to traditional manual decision-making methods, completely solving the problems of reliance on manual and low efficiency in operational decisions. These four synergistic effects enable public communication networks to achieve "highly smooth and highly intelligent operation and maintenance," achieving a qualitative improvement in link stability and operational efficiency compared to existing technologies, fully meeting the needs of public communication networks.

[0039] Existing technologies employ a "fixed link parameters + manual inspection + manual decision-making" model, lacking dynamic link status identification, adaptive link parameter adjustment, accurate diagnosis of operational anomalies, and intelligent generation of operational decisions. This results in passive link adjustment, low operational efficiency, and delayed anomaly handling, failing to meet the high-smoothness and high-efficiency operational requirements of public communication networks and easily leading to poor user experience and high operational costs. This embodiment, through innovation and model optimization, achieves adaptive link adjustment and intelligent operational decision-making for public communication networks, completely resolving the pain points of existing technologies. Link stability, transmission efficiency, anomaly diagnosis accuracy, and operational decision adaptability all meet public communication network standards. Furthermore, it does not overlap with existing technologies, current technical directions, or implementation scenarios, highlighting its innovation, strong practicality, and aligning with the development needs of strategic emerging industries.

[0040] Example 3: Private Network Communication Link Adaptation and Data Encryption Scenario (corresponding to link adaptive adjustment and data transmission encryption module) Implementation steps Step 1: Data Acquisition and Scenario Adaptation: Collect link status data, service transmission requirement data (private network scheduling, confidential transmission), interference data, communication data characteristics, encryption requirement data, and security level data for private network communication scenarios. Adapt to the "high stability and high security" requirements of private network communication and build a link adjustment and data encryption resource pool.

[0041] Step 2: Link Adaptive Adjustment: By adopting dynamic link status identification and adaptive adjustment of link parameters, the characteristics of link status, interference and service requirements are extracted, a link status identification and parameter adjustment model is constructed, and link parameters are dynamically adjusted and interference is suppressed to achieve link adaptive adaptation, ensuring stable transmission and low latency requirements of private network communication.

[0042] Step 3: Dynamic generation of data encryption keys: The data encryption key is dynamically generated by extracting data features, timestamps and security level features, constructing a key generation model, and combining it with the key generation calculation formula to generate dynamic encryption keys. The keys are then security verified to ensure their security and timeliness, adapting to the confidential transmission requirements of private networks.

[0043] Step 4: Data Hierarchical Encryption Transmission: Data hierarchical encryption transmission is adopted. Based on the data security level, a data hierarchical encryption model is constructed. High-strength encryption strategy is used for confidential scheduling data of the private network, and efficient encryption strategy is used for ordinary private network data to achieve secure and efficient data transmission and ensure the security of private network communication.

[0044] Step 5: Continuous optimization: Verify link stability, transmission efficiency, key security, and encryption efficiency; collect data on changes in the needs of private network communication scenarios, optimize parameters and adjustments, and encryption strategies to improve adaptability to high-stability and high-security scenarios of private network communication.

[0045] Modeling Innovation Principles Abandoning the traditional, crude modeling approach of "fixed link parameters, fixed keys, and unified encryption," this paper constructs an integrated closed-loop model of "link adjustment - key generation - hierarchical encryption." It takes the high stability and security requirements of private network communication, link characteristics, data characteristics, and security levels as core inputs, overcoming the limitations of passive link adjustment and rigid data encryption. Link adjustment modeling achieves dynamic adaptation of link parameters and interference suppression; key generation modeling achieves dynamic generation and security verification of encryption keys; and hierarchical encryption modeling achieves differentiated encryption of data at different security levels, filling the gap in integrated modeling of link adaptation and data encryption for private network communication. The modeling process focuses on the high stability and high security requirements of private network communication scenarios, completely different from the fixed parameter and fixed key modeling approaches and technical directions of existing technologies, and has no overlap with the current modeling logic. It represents a completely new modeling direction, aligning with the development needs of emerging strategic industries such as new mobile communication networks and cybersecurity.

[0046] Dynamic link status identification, through link characteristics, interference characteristics, and service requirements modeling and dynamic identification strategies, significantly improves the accuracy of link status identification and the timeliness of anomaly prediction compared to the traditional fixed parameter mode, completely solving the problems of inaccurate link status identification and inability to predict anomalies, providing stable link support for private network communication; adaptive link parameter adjustment, through link status, service requirements, and parameter adjustment modeling and dynamic adjustment strategies, significantly improves link stability, transmission efficiency, and interference resistance compared to the traditional fixed parameter mode, completely solving the problems of link congestion and weak interference resistance, meeting the low latency requirements of private networks; dynamic data encryption key generation, through data characteristics, timestamps, and security, etc. The hierarchical modeling and key generation calculation formula significantly improves key security, uniqueness, and timeliness compared to the traditional fixed key mode, completely solving the problem of easy key cracking and ensuring the security of confidential data on the private network. The hierarchical encrypted data transmission, through data security levels, encryption requirements, hierarchical encryption modeling, and differentiated encryption strategies, significantly improves encryption efficiency and data transmission security compared to the traditional unified encryption mode, completely solving the problems of single encryption strategies and low encryption efficiency. These four synergistic effects enable the private network communication to achieve "high stability and high security." Compared to existing technologies, link stability, data security, and transmission efficiency are qualitatively improved, fully meeting the high stability and high security requirements of private network communication.

[0047] Existing technologies employ a "fixed link parameters + fixed key + unified encryption" model, lacking dynamic link status identification, adaptive link parameter adjustment, dynamic generation of data encryption keys, and hierarchical encrypted data transmission. This results in passive link adjustment and rigid data encryption, failing to meet the high stability and security requirements of private network communication and easily leading to security risks such as link interruptions and data leaks. This embodiment, through innovation and modeling optimization, achieves adaptive link adjustment and data transmission encryption for private network communication, completely resolving the pain points of existing technologies. Link stability, transmission efficiency, key security, and encryption efficiency all meet private network communication standards, and there is no overlap with existing technologies, current technical directions, or implementation scenarios. Its innovation is prominent, its practicality is strong, and it aligns with the development needs of strategic emerging industries.

[0048] Example 4: Multi-scenario converged communication automated management and control platform (industrial + public + private network) scenario (integrating three core modules) Implementation steps Step 1: Link Adaptive Adjustment: Collect link status data, multi-scenario service transmission requirement data, and interference data from the multi-scenario fusion platform. Use two components of the link adaptive adjustment module to dynamically adjust link parameters and suppress interference, achieving adaptive adaptation of links in multiple scenarios. Output the link adaptive adjustment scheme to ensure smooth communication transmission in multiple scenarios.

[0049] Step 2: Data Transmission Encryption: Collect platform communication data characteristics, encryption requirements, and security level data. Utilize two aspects of the data transmission encryption module, combined with the key generation calculation formula, to generate a dynamic encryption key. This achieves hierarchical encryption and secure transmission of data, outputting a data encryption transmission strategy to ensure data security in multiple scenarios.

[0050] Step 3: Intelligent Operation and Maintenance Decision-Making: Collect platform equipment operation data, link anomaly data, and operation and maintenance requirement data. Utilize two components of the intelligent operation and maintenance decision-making module to achieve accurate diagnosis of operation and maintenance anomalies and intelligent generation of operation and maintenance solutions. Output an operation and maintenance decision report to ensure stable operation of communication in multiple scenarios.

[0051] Step 4: Multi-module collaborative management and control: The three core modules achieve real-time data interaction through high-speed communication links, integrate the results of link adjustment, data encryption, and operation and maintenance decisions, and output the full-domain collaborative management and control instructions of the multi-scenario fusion platform to achieve collaborative management and control of multiple scenarios, multiple links, and multiple data, ensuring the stable, efficient, and secure operation of the platform.

[0052] Step 5: Full-process verification and optimization: Verify link stability, transmission efficiency, key security, encryption efficiency, anomaly diagnosis accuracy, and operational decision adaptability; collect business feedback from various scenarios; optimize the parameters and control strategies of the three major modules; realize continuous optimization and scenario expansion of automated collaborative management and control of platform communication; meet the needs of strategic emerging industries for multi-scenario integration, high efficiency, and secure development; and meet the requirements of the invention priority examination policy.

[0053] Modeling Innovation Principles Abandoning the traditional, crude modeling approach of "independent modules and single-level control," this paper constructs an integrated, full-domain modeling logic encompassing "link adjustment, data encryption, operation and maintenance decision-making, and multi-module fusion." It uses the multi-service requirements, link characteristics, data characteristics, equipment operation characteristics, and security requirements of a multi-scenario fusion platform as core inputs, overcoming the limitations of traditional communication automation modules being independent and lacking coordination. The deep integration of these three core modules achieves closed-loop control of the entire process from link adjustment to encryption and operation and maintenance. Link adjustment modeling enables efficient adaptation of links across multiple scenarios, data encryption modeling ensures secure data transmission across multiple scenarios, and operation and maintenance decision-making modeling achieves intelligent and efficient operation and maintenance across multiple scenarios, filling the gap in full-domain modeling for multi-scenario fusion communication automation management and control platforms. The modeling process focuses on the multi-scenario fusion, efficiency, security, and intelligent development needs of strategic emerging industries, completely differing from the single-module, single-scenario modeling approach and technical direction of existing technologies. It also has no overlap with the current modeling logic, representing a completely new modeling direction that complies with the policy requirements for priority examination of inventions.

[0054] The six core aspects of this invention achieve synergistic efficiency in a multi-scenario converged communication automated management and control platform: Two aspects of link adjustment enable adaptive adaptation and interference suppression of links across multiple scenarios. Compared to traditional independent link adjustment modes, link stability, transmission efficiency, and interference resistance are significantly improved, effectively ensuring smooth communication across multiple scenarios. Two aspects of data encryption enable dynamic encryption and hierarchical transmission of data across multiple scenarios. Compared to traditional independent data encryption modes, key security, encryption efficiency, and data transmission security are significantly improved, effectively ensuring data security across multiple scenarios. Two aspects of operation and maintenance decision-making enable accurate diagnosis and intelligent decision-making for operation and maintenance anomalies across multiple scenarios. Compared to traditional independent operation and maintenance modes, the accuracy of anomaly diagnosis and the efficiency of operation and maintenance decision-making are significantly improved, effectively reducing operation and maintenance costs across multiple scenarios. These six aspects, working in conjunction with the three main modules, achieve comprehensive optimization of the multi-scenario converged communication automated management and control platform, achieving "high stability, high security, and high intelligence." Compared to existing technologies, the level of communication automation and collaborative management and control represents a qualitative leap, fully meeting the high-efficiency, secure, and intelligent needs of multi-scenario converged communication in strategic emerging industries, and complying with the requirements of the invention priority examination policy of "promoting industrial transformation and upgrading, enhancing core industrial competitiveness, and ensuring network security."

[0055] Existing communication automation methods suffer from problems such as independent and singular modules, lack of collaborative management and control, and absence of dynamic link status identification, adaptive adjustment of link parameters, dynamic generation of data encryption keys, hierarchical encrypted data transmission, accurate diagnosis of operational anomalies, and intelligent generation of operational decisions. They also suffer from poor adaptability of multi-scenario integrated communication links, rigid data encryption, and low operational efficiency, making it difficult to meet the high stability, high security, high intelligence, and multi-service requirements of multi-scenario integrated communication automation management platforms. This embodiment, through three core modules and six core integrated innovations, achieves adaptive encryption of communication links and intelligent operational decisions, completely solving the pain points of existing technologies. It significantly improves the stability of multi-scenario communication links, data security, and the level of operational intelligence, and has no overlap with existing technologies, current technical directions, or implementation scenarios. Its innovations are prominent, its practicality is strong, and it can be widely applied to various communication automation scenarios such as industrial, public, and private networks.

[0056] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A link adaptive encryption and intelligent operation and maintenance decision-making method for communication automation, characterized in that, Includes the following steps: S1: Link adaptive adjustment processing, collects communication link status data, service transmission demand data and interference data, and achieves accurate identification of link status, dynamic adaptation of parameters and interference suppression through dynamic identification of link status and adaptive adjustment of link parameters, and outputs link adaptive adjustment scheme. S2: Data transmission encryption processing, collecting communication data characteristics, encryption requirement data and security level data, and realizing dynamic generation of encryption keys, hierarchical encryption and secure transmission of data through dynamic generation of data encryption keys and hierarchical encryption transmission of data, and outputting data encryption transmission strategy; S3: Intelligent decision processing for operation and maintenance. It collects communication equipment operation data, link anomaly data and operation and maintenance requirement data. Through accurate diagnosis of operation and maintenance anomalies and intelligent generation of operation and maintenance decisions, it realizes accurate diagnosis of operation and maintenance anomalies, intelligent generation of operation and maintenance solutions and closed-loop execution, forming a closed loop of communication automation full-process link-encryption-operation and maintenance collaborative management and control. In step S2, the dynamic generation of the data encryption key includes a key generation calculation formula, which is as follows: The constraints are , For dynamically generated encryption keys, For hash encryption functions, , , These are data characteristics, timestamps, and security level impact coefficients, respectively. ), Quantization values ​​for communication data characteristics Quantized value for timestamp, As a quantification value for the security level, This is the key entropy value. This is the threshold value for key security entropy, set according to the data security level.

2. The method according to claim 1, characterized in that, The dynamic identification of link status in step S1 includes the following sub-steps: extracting link status features, interference features and service transmission requirement features, constructing a link status identification modeling system, and realizing accurate identification, anomaly prediction and type classification of link status.

3. The method according to claim 1, characterized in that, The adaptive adjustment of link parameters in step S1 is based on the link status identification results and service transmission requirements. A link parameter adjustment model is constructed to dynamically adjust the link bandwidth, encoding method and transmission rate, so as to achieve link adaptive adaptation and interference suppression.

4. The method according to claim 1, characterized in that, The dynamic generation of the data encryption key in step S2 involves extracting data features, timestamps, and security level features to construct a key generation model. Combined with the key generation calculation formula, this enables the dynamic generation and security verification of the encryption key, ensuring key uniqueness and security.

5. The method according to claim 1, characterized in that, The data hierarchical encryption transmission in step S2 is based on data security level and encryption requirements. A data hierarchical encryption model is constructed, and differentiated encryption strategies are adopted for data with different security levels to achieve secure and efficient data transmission.

6. The method according to claim 1, characterized in that, The precise diagnosis of operation and maintenance anomalies in step S3 involves extracting equipment operation characteristics and link anomaly characteristics, constructing an operation and maintenance anomaly diagnosis model, and realizing the precise location, type identification, and severity assessment of operation and maintenance anomalies.

7. The method according to claim 1, characterized in that, The intelligent generation of operation and maintenance decisions in step S3 is based on the anomaly diagnosis results and operation and maintenance requirements. It constructs an operation and maintenance decision model, intelligently generates an appropriate operation and maintenance solution, and realizes accurate, efficient and closed-loop execution of operation and maintenance decisions.

8. The method according to claim 1, characterized in that, The key security entropy threshold It can be flexibly adjusted according to the data security level, core confidential data Ordinary confidential data Ordinary data The impact coefficient can be dynamically adjusted based on data characteristics and security requirements.

9. The method according to any one of claims 1-8, characterized in that, The method can be applied to communication automation scenarios such as industrial-grade communication, public communication, private network communication, and smart grid communication, enabling link adaptive adjustment, data transmission encryption, and intelligent operation and maintenance decision-making.

10. A communication automation link adaptive encryption and intelligent operation and maintenance decision-making system, characterized in that, include: The system comprises a link adaptive adjustment module, a data transmission encryption module, an operation and maintenance intelligent decision-making module, a multi-source data acquisition module, and a collaborative management and control engine module. The link adjustment module executes the functions of claims 1-2, the encryption module executes the functions of claims 4-5, and the operation and maintenance decision-making module executes the functions of claims 6-7. Each module achieves real-time data interaction through a high-speed communication link, thereby completing automated communication, link adaptive encryption, and intelligent operation and maintenance decision-making.

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