Method, device and equipment for controlling display terminal through dynamic code matching and storage medium

Abstract

The invention relates to the technical field of display control, and discloses a method and device for controlling a display terminal through dynamic code matching, equipment and a storage medium. The method comprises the following steps: integrating various parameters of a code matching rule base, a code matching generator and a display terminal, and constructing a dynamic code matching system; obtaining input data of the display terminal based on the dynamic code matching system, and preprocessing and analyzing the input data to obtain a metadata structure containing data attributes and processing marks; carrying out code matching rule matching and parameter adjustment to obtain a configuration object containing a coding algorithm and key information; carrying out segmentation, transformation, encryption and mapping processing on the input data to obtain a coding data packet containing coding data and decoding information; performing fragmentation and secondary encryption processing to obtain a plurality of encrypted data fragments; according to the method and the device, the content of the display terminal can be safely and flexibly controlled by the aid of the method and the device, and the content of the display terminal can be safely and flexibly controlled by the aid of the method and the device.

Description

Technical Field

[0001] The present application relates to the field of display control technology, and in particular to a method, device, equipment and storage medium for dynamically matching codes to control a display terminal. Background Art

[0002] Display terminals have become an important medium for people to obtain and exchange information. However, with the increasing number of information security threats, how to achieve efficient display control while ensuring data transmission security has become an urgent problem to be solved. Traditional display control methods often use fixed encoding and encryption strategies, which are difficult to adapt to different types of data and diverse display terminals, and are also unable to effectively cope with complex and changing network environments and security threats.

[0003] Although some existing dynamic encoding methods have improved the security of data transmission to a certain extent, they generally have problems such as complex configuration, high performance overhead, and poor adaptability. Especially when facing large-scale, highly dynamic display terminal groups, these methods often fail to meet the requirements of real-time and flexibility. In addition, the existing methods are not intelligent enough in data preprocessing, encoding rule matching, encryption strategy selection, etc., and it is difficult to automatically optimize configuration parameters according to data characteristics and terminal conditions, resulting in low overall system efficiency. Summary of the invention

[0004] The present application provides a method, apparatus, device and storage medium for dynamically matching codes to control a display terminal, which are used to achieve secure and flexible control of the content of the display terminal.

[0005] In a first aspect, the present application provides a method for dynamically matching a code to control a display terminal, the method comprising: Integrate and process the parameters of the coding rule library, coding generator and display terminal to build a dynamic coding system; Based on the dynamic code matching system, the input data of the display terminal is acquired, and the input data is preprocessed and analyzed to obtain a metadata structure including data attributes and processing marks; Calling the coding rule library to perform coding rule matching and parameter adjustment on the metadata structure to obtain a configuration object including coding algorithm and key information; Based on the configuration object and the matching code generator, the input data is segmented, transformed, encrypted and mapped to obtain a coded data packet containing coded data and decoding information; Slicing and re-encrypting the encoded data packet to obtain a plurality of encrypted data slices; The plurality of encrypted data fragments are multi-path transmitted and reassembled to obtain reassembled data, and the reassembled data is decoded and presented on the display terminal.

[0006] In a second aspect, the present application provides a device for dynamically matching a code to control a display terminal, the device for dynamically matching a code to control a display terminal comprising: The construction module is used to integrate and process the parameters of the coding rule base, coding generator and display terminal to build a dynamic coding system; An acquisition module, used for acquiring input data of the display terminal based on the dynamic coding system, and preprocessing and analyzing the input data to obtain a metadata structure including data attributes and processing marks; A matching module, used to call the coding rule library to perform coding rule matching and parameter adjustment on the metadata structure to obtain a configuration object including a coding algorithm and key information; A processing module, used to segment, transform, encrypt and map the input data based on the configuration object and the matching code generator to obtain a coded data packet containing coded data and decoding information; An encryption module, used for performing fragmentation and secondary encryption processing on the encoded data packet to obtain a plurality of encrypted data fragments; The reassembly module is used to perform multi-path transmission and reassembly on the multiple encrypted data fragments to obtain reassembled data, and decode and present the reassembled data on the display terminal.

[0007] The third aspect of the present application provides a device for dynamically matching code to control a display terminal, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the device for dynamically matching code to control a display terminal executes the above-mentioned method for dynamically matching code to control a display terminal.

[0008] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned method for dynamically matching codes to control a display terminal.

[0009] In the technical solution provided by the present application, by integrating the coding rule library, the coding generator and the display terminal parameters, the dynamic call and update of the coding rules are realized, the input data is analyzed and processed in multiple dimensions, and a metadata structure containing rich semantic information is generated. Based on the metadata structure, rule matching and parameter adjustment are performed to realize the dynamic selection of the encoding algorithm and encryption scheme. Through multiple processing such as segmentation, transformation, encryption and mapping, the security and transmission efficiency of the data are improved, and the reversibility of the data is guaranteed. The coded data packets are unevenly fragmented and dynamically encrypted, which enhances the security of data transmission, realizes the priority transmission and distributed transmission of data fragments, improves the transmission efficiency and anti-interference ability, and ensures the integrity of the data. Decoding and rendering optimization are performed according to the characteristics of the display terminal to ensure the best display effect of the decoded data on different terminals. By dynamically adjusting the encoding algorithm and parameters, as well as the intelligent fragmentation and transmission strategy, efficient utilization of computing resources and network bandwidth is achieved, thereby realizing the security and flexible control of the content of the display terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0011] Figure 1 A schematic diagram of an embodiment of a method for dynamically matching codes to control a display terminal in an embodiment of the present application; Figure 2 Schematic diagram of an embodiment of a device for dynamically matching codes to control a display terminal in an embodiment of the present application. DETAILED DESCRIPTION

[0012] The embodiments of the present application provide a method, device, equipment and storage medium for dynamically matching code to control display terminals. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0013] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 , an embodiment of the method for dynamically matching codes to control a display terminal in an embodiment of the present application includes: Step S101, integrating and processing various parameters of the code matching rule library, the code matching generator and the display terminal to construct a dynamic code matching system; It is understandable that the execution subject of the present application may be a device for dynamically matching code to control the display terminal, or may be a terminal or a server, which is not limited here. The present application embodiment is described by taking the server as the execution subject as an example.

[0014] Specifically, a variety of encoding algorithms, encryption schemes and mapping rules are classified and sorted, and each algorithm and scheme is analyzed to extract applicable scenarios and characteristics, and on this basis, a matching rule library is constructed. Based on the matching rule library, the internal rules are prioritized and associated, forming a logically rigorous and efficient matching rule network, so that the optimal rule combination can be quickly found in the subsequent call process. The matching rule network is indexed and associated to obtain a rule index tree. The rule index tree serves as the basis for the initialization setting of the matching engine, ensuring that the initial generator can dynamically and accurately access the adaptation rules in the rule library when calling. The hardware parameters and software configuration parameters of the display terminal are collected, and these parameters are standardized to generate a standardized terminal parameter set. The parameter set is used to optimize the performance and adapt the matching engine to ensure that the matching generator can make full use of the resources and capabilities of the display terminal to achieve the best encoding and encryption effect. In order to verify the matching degree between the matching rule library and the matching generator, cross-validation is performed to generate a rule-generator matching matrix. Based on the rule-generator matching matrix, a dynamic update mechanism is configured for the matching rule base, and an adaptive rule update strategy is formulated. This strategy ensures that the matching rule base can be self-updated and optimized as the environment and needs change, maintaining the efficiency and adaptability of the system. The adaptive rule update strategy is integrated with the matching generator and globally optimized to build an efficient, flexible and intelligent dynamic matching system. Through the dynamic matching system, the display terminal can achieve efficient processing and secure transmission of input data, improving the overall user experience and data security.

[0015] Step S102: obtaining input data of the display terminal based on the dynamic coding system, and preprocessing and analyzing the input data to obtain a metadata structure including data attributes and processing marks; Specifically, in the dynamic coding system, the input interface of the display terminal is monitored in multiple threads to ensure that various types of input data can be captured and processed in real time. The captured input data is classified and divided into multiple typed data sets, including text data, image data, audio and video data, etc. For text data, word segmentation and semantic analysis are performed. Through natural language processing technology, the text is decomposed into basic vocabulary units, and the semantic relationship therein is identified to form a structured text representation. For image data, feature extraction and target detection are performed to identify the key feature points and target objects in the image, and the corresponding feature vector representation is generated. For audio and video data, the codec format conversion is performed to convert it into a standardized processing format. A multidimensional feature vector is constructed based on the standardized processing results, and the high-dimensional feature vector is reduced to a more compact feature descriptor through feature dimensionality reduction technology. Cluster analysis and anomaly detection are performed on the feature descriptors. Through cluster analysis, the distribution characteristics of the data are identified and potential anomaly markers are found. Based on the anomaly markers, the input data is adaptively sampled and noise filtered to optimize the quality of the data sample and ensure the accuracy and reliability of subsequent analysis. For the optimized data samples, time series analysis and spatial correlation calculation are performed. Through time series analysis, the changing patterns of data in the time dimension are identified, while spatial correlation calculation reveals the correlation of data in the spatial dimension. Based on the description of spatiotemporal features, a data dependency graph is constructed to show the dependencies and transmission paths between data. On this basis, the data dependency graph is topologically sorted and path analyzed to determine the priority strategy for data processing. Based on the data processing priority strategy, the input data is divided into blocks and hash-coded, divided into multiple data blocks, and each data block is hash-coded to generate a unique identifier. Metadata extraction and semantic annotation are performed on the data block set to generate a metadata structure containing data attributes and processing tags.

[0016] Step S103: calling the coding rule library to perform coding rule matching and parameter adjustment on the metadata structure to obtain a configuration object including the coding algorithm and key information; Specifically, the metadata structure is analyzed, and a preliminary screening is performed from the coding rule library according to its characteristics to filter out a set of rules that best match the input data to form a set of candidate rules. The candidate rules are weighted and scored. The scoring criteria include multiple dimensions such as the applicability, efficiency, and security of the rules. A rule ranking list is formed through comprehensive scoring. On this basis, the rule combination with the highest score is selected, and compatibility analysis and conflict detection are performed on it to ensure that the selected rules can work together seamlessly to form an optimized rule chain. A rule decision structure is generated based on the optimized rule chain, which defines the execution order and logical relationship of the rules. A parameter sensitivity analysis is performed on the rule decision structure to determine which parameters have the greatest impact on the rule execution effect, and a parameter adjustment strategy is formulated. In the actual execution process, the strategy is dynamically adjusted according to the changes in the input data to ensure that the rule decision is always in the optimal state. Under the guidance of the parameter adjustment strategy, an adapted initial encryption scheme is selected from the encryption algorithm library, and the corresponding key information is generated. In order to ensure that the generated key information has sufficient security strength and performance, a comprehensive security strength evaluation and performance test are performed on it. These tests include key length, encryption strength, processing speed and other aspects. Through these test results, the target encryption scheme is optimized and finally determined. The rule decision structure, key information and target encryption scheme are integrated and packaged to form a complete configuration object. The configuration object contains the encoding algorithm and key information, which can guide the dynamic code control display terminal to perform efficient and secure data processing and transmission.

[0017] Step S104: based on the configuration object and the code generator, the input data is segmented, transformed, encrypted and mapped to obtain a coded data packet containing coded data and decoding information; Specifically, according to the configuration object, the input data is adaptively divided into blocks to obtain multiple data sub-blocks. By analyzing the characteristics and content of the input data, the block strategy is dynamically adjusted to ensure that the size and number of the data sub-blocks are suitable for subsequent processing. Fourier transform and wavelet transform are performed on each data sub-block to obtain feature representation. These feature representations can effectively capture the frequency and time domain information in the data. According to these characteristics, the optimal transformation basis is selected for sparse representation, the data structure is compressed, and efficient compressed data is obtained. Multiple rounds of permutation and diffusion operations are performed on the compressed data structure to enhance the degree of obfuscation of the data and obtain preliminary encrypted data. Based on the key information in the configuration object, a pseudo-random sequence is generated, and an XOR operation is performed on the preliminary encrypted data to obtain enhanced encrypted data. The unpredictability of the pseudo-random sequence is used to improve the security of the data. According to the mapping rules of the matching code generator, the enhanced encrypted data is spatially mapped and color transformed to obtain the first coded data adapted to the display terminal. The data is converted into a format suitable for presentation by the display terminal through the mapping rules to ensure that the data can be displayed correctly. The first coded data is reversibly watermarked to obtain the second coded data with hidden information. Reversible watermark embedding technology can not only embed additional information without affecting data quality, but also completely restore the original data when necessary. Based on the encoding algorithm in the configuration object, the second encoded data with hidden information is entropy encoded and redundantly encoded to obtain compressed encoded data. Entropy encoding and redundant encoding technologies improve encoding efficiency and data compression ratio by reducing data redundancy. After the data encoding is completed, the initial decoding information is created, which contains transformation parameters, encryption keys, mapping rules and encoding methods. The initial decoding information is digitally signed to obtain authenticated decoding information. Digital signature technology verifies the source and integrity of data through encryption to prevent data from being tampered with during transmission. The compressed encoded data and the authenticated decoding information are packaged, and the checksum and version information are added to obtain an encoded data packet containing the encoded data and the decoding information. The checksum is used to detect errors that may occur during data transmission, and the version information helps the receiving end identify the format and processing method of the data packet.

[0018] Step S105, fragmenting and re-encrypting the encoded data packet to obtain a plurality of encrypted data fragments; Specifically, the data structure of the encoded data packet is analyzed, and the semantics and importance of the data are identified by analyzing the internal structure of the encoded data packet, and the data is layered according to the information to obtain a multi-layer data structure. Based on the multi-layer data structure, the encoded data packet is unevenly fragmented. Uniform fragmentation can divide the data packet into multiple original data fragments according to the importance and semantic information of the data. Important data may be subdivided into smaller fragments to increase its redundancy and security, while minor data can be merged into larger fragments, thereby optimizing the efficiency and reliability of data transmission. A unique fragment identifier is generated for each original data fragment, and a dependency graph between each original data fragment is constructed to obtain a fragment set with topological information. The dependency graph can describe the dependency relationship and logical order between each data fragment, ensuring that the structure and content of the original data packet can be correctly restored in the subsequent processing and transmission process. On this basis, the fragment set with topological information is shuffled and rearranged to obtain a random fragment sequence. The order of the original data fragments is disrupted to increase the security of the data packet, making it difficult for unauthorized recipients to reassemble and decode the data. Dynamic key generation is performed for each original data shard in the random shard sequence. According to the specific algorithm and current security requirements, a unique encryption key is generated for each shard to obtain a shard-key correspondence table. According to the shard-key correspondence table, secondary encryption is performed on each original data shard in the random shard sequence. The secondary encryption process uses the dynamically generated key to perform independent encryption operations on each data shard to enhance data security. Finally, multiple encrypted data shards are obtained, which have high anti-attack capabilities and data integrity during transmission.

[0019] Step S106: perform multi-path transmission and reorganization on the multiple encrypted data slices to obtain reorganized data, and decode and present the reorganized data on the display terminal.

[0020] Specifically, the transmission priority of multiple encrypted data slices is evaluated to generate a priority transmission queue. By analyzing the importance and time sensitivity of the content of each slice, the transmission priority is determined to ensure that key data is transmitted first. The network environment is detected and evaluated in real time according to the priority transmission queue to generate a multi-path transmission scheme. By real-time monitoring of the current network environment, the transmission performance and reliability of different paths are evaluated, and the optimal path is selected for data transmission to improve transmission efficiency and data security. Based on the multi-path transmission scheme, network protocol encapsulation and transmission encryption are performed on each encrypted data slice to form a distributed transmission encrypted data stream. Each slice is encapsulated in an appropriate network protocol before transmission, and encryption technology is used to protect the security of data during transmission. In the display terminal, the distributed transmission encrypted data stream is received, and decapsulation and integrity verification are performed. Decapsulation restores the received data stream to the original encrypted data slice, and integrity verification ensures that the data is not tampered with or lost during transmission through technologies such as checksum. Through these steps, a valid encrypted data slice set is obtained. The valid encrypted data slice set is sorted and missing detection is performed to ensure that all slices are arranged in the correct order and detect whether there are missing slices. After sorting and detection, a complete encrypted data fragment sequence is obtained. The complete encrypted data fragment sequence is reorganized and spliced ​​to restore the data packet to be decrypted. A complete data packet is formed by re-splicing the fragments in the original order. The data packet to be decrypted is decrypted in multiple layers, and the encryption layer is removed layer by layer until the encoded data and decoding information are restored. Based on the algorithm parameters and keys in the decoding information, the encoded data is decoded to restore the original input data. The decoding step is reversed according to the algorithm and key used during encoding to ensure that the data is completely restored. The input data is format converted and rendered to adapt to the format requirements of the display terminal. Rendering optimization includes adjusting the color, resolution and other aspects of the data to ensure the best effect on the display terminal. According to the hardware parameters and software configuration parameters of the display terminal, the data is color corrected and the resolution is adjusted. Color correction ensures that the displayed color is accurate, and resolution adjustment makes the data match the resolution of the display terminal to avoid distortion and blur. The display data adapted to the display terminal is transmitted to the graphics processing unit of the display terminal, and the image is synthesized and displayed by the graphics processing unit. The graphics processing unit synthesizes the processed image data and presents the final image to the display terminal through the display buffer, ensuring that the decoded content is displayed to the user in a high-quality form.

[0021] In the embodiment of the present application, by integrating the coding rule library, the coding generator and the display terminal parameters, the dynamic call and update of the coding rules are realized, the input data is analyzed and processed in multiple dimensions, and a metadata structure containing rich semantic information is generated. Based on the metadata structure, rule matching and parameter adjustment are performed to realize the dynamic selection of coding algorithms and encryption schemes. Through multiple processing such as segmentation, transformation, encryption and mapping, the security and transmission efficiency of data are improved, and the reversibility of data is guaranteed. The coded data packets are unevenly fragmented and dynamically encrypted, which enhances the security of data transmission, realizes the priority transmission and distributed transmission of data fragments, improves the transmission efficiency and anti-interference ability, and ensures the integrity of data. Decoding and rendering optimization are performed according to the characteristics of the display terminal to ensure the best display effect of decoded data on different terminals. By dynamically adjusting the coding algorithm and parameters, as well as the intelligent fragmentation and transmission strategy, efficient utilization of computing resources and network bandwidth is achieved, thereby realizing the security and flexible control of the content of the display terminal.

[0022] In a specific embodiment, the process of executing step S101 may specifically include the following steps: (1) Classify and organize various encoding algorithms, encryption schemes, and mapping rules to obtain a coding rule base, and perform rule priority sorting and association analysis on the coding rule base to obtain a coding rule network; (2) Indexing and association analysis are performed on the coding rule network to obtain a rule index tree. Based on the rule index tree, the initial generator is initialized to obtain a coding engine that can dynamically call rules. (3) Collect and standardize the hardware parameters and software configuration parameters of the display terminal to obtain a standardized terminal parameter set, and optimize and adapt the coding engine according to the standardized terminal parameter set to obtain a coding generator; (4) Cross-validate the coding rule base and the coding generator to obtain the rule-generator matching matrix, and configure the dynamic update mechanism of the coding rule base based on the rule-generator matching matrix to obtain the adaptive rule update strategy; (5) Integrate and globally optimize the adaptive rule update strategy and code generator to build a dynamic code system.

[0023] Specifically, various encoding algorithms, encryption schemes and mapping rules are classified and organized. Encoding algorithms include common Huffman encoding, Shannon-Fano encoding, LZW encoding, etc. Encryption schemes cover symmetric encryption (such as AES, DES) and asymmetric encryption (such as RSA, ECC). Mapping rules involve data format conversion, image mapping rules, etc. These algorithms and rules are systematically organized according to categories, application scenarios, advantages and disadvantages to form a preliminary coding rule library. In order to better use these rules, they are prioritized. The priority is calculated using the following formula: ; in, It is The priority of the rules, is the efficiency of the rules, It is the security of the rules, is the complexity of the rule, are the corresponding weights. These weights are adjusted according to the actual application requirements. For example, in an application with high security requirements, will be set higher. Through priority sorting and association analysis between rules, a coding rule network is formed. The network shows the dependencies and priorities between the rules, which facilitates the rapid search and application of rules in subsequent steps. The coding rule network is indexed and associated, and a rule index tree is obtained. The rule index tree structuredly represents all the rules and their relationships in the coding rule network, which is helpful for rapid query and matching. Through the rule index tree, the initial generator is initialized to ensure that the coding engine can dynamically call these rules to achieve flexible and intelligent coding operations. The hardware parameters and software configuration parameters of the display terminal are collected and standardized. For example, hardware parameters include CPU and GPU performance indicators, memory size, display resolution, etc.; software configuration parameters include operating system version, supported codec format, etc. Through standardization, a standardized terminal parameter set is generated. According to the standardized terminal parameter set, the coding engine is optimized and adapted to form a coding generator. For example, on a display terminal with a high-performance GPU, a coding algorithm that is computationally intensive but has better compression effect may be selected, while a simple and efficient algorithm may be selected on a low-performance terminal. The optimization process may include algorithm parameter adjustment, parallel computing optimization, etc. Cross-validate the matching rule base and matching generator to generate a rule-generator matching matrix. The matrix shows the matching degree between different rules and generators, helping to identify the optimal combination. For example, in a specific application, it may be found that the AES encryption scheme and Huffman coding perform best on the terminal. Through this matching matrix, the matching rule base is dynamically updated to form an adaptive rule update strategy. This strategy ensures that the rule base can be dynamically adjusted according to actual usage, such as adding new encoding algorithms and removing outdated encryption schemes. Integrate and globally optimize the adaptive rule update strategy and matching generator to build a dynamic matching system. The system can intelligently select the optimal encoding and encryption schemes according to the characteristics of different terminals, and adjust in real time to adapt to the changing network and computing environment. For example, when the network condition deteriorates, the system can automatically switch to a more robust transmission protocol. After the terminal hardware is upgraded, the system can use more advanced encoding technology to improve efficiency.

[0024] In a specific embodiment, the process of executing step S102 may specifically include the following steps: (1) Based on the dynamic coding system, the input interface of the display terminal is monitored in multiple threads to obtain input data; (2) Classify the input data to obtain multiple typed data sets, perform word segmentation and semantic analysis on the text data in the typed data sets, perform feature extraction and target detection on the image data in the typed data sets, and perform codec format conversion on the audio and video data in the typed data sets to obtain standardized processing results; (3) Construct a multidimensional feature vector based on the standardized processing results, and perform feature dimensionality reduction on the multidimensional feature vector to obtain a feature descriptor; (4) Perform cluster analysis and anomaly detection on feature descriptors to obtain data distribution characteristics and potential anomaly markers. Based on the data distribution characteristics and anomaly markers, perform adaptive sampling and noise filtering on the input data to obtain optimized data samples. (5) Perform time series analysis and spatial correlation calculation on the optimized data samples to obtain spatiotemporal feature descriptions, and construct a data dependency graph based on the spatiotemporal feature descriptions. Perform topological sorting and path analysis on the data dependency graph to obtain a data processing priority strategy. (6) Based on the data processing priority strategy, the input data is divided into blocks and hash-encoded to obtain a data block set, and metadata is extracted and semantically annotated on the data block set to obtain a metadata structure containing data attributes and processing tags.

[0025] Specifically, the input interface of the display terminal is monitored by multiple threads based on the dynamic coding system, and multiple threads are created to monitor different input interfaces of the display terminal to ensure that all input data can be captured and processed in real time. These input data may include different types such as text, images, audio and video. Each thread will work independently to capture and cache input data to ensure the real-time and efficiency of data processing. The input data is classified and divided into multiple typed data sets. The basis for classification includes the format, source and purpose of the data. For example, text data is classified into a text data set, image data is classified into an image data set, and audio and video data is classified into an audio and video data set. The text data is segmented and semantically analyzed. Through natural language processing technology, the text is decomposed into basic vocabulary units, and the semantic relationship between words is identified to extract the main information and emotional tendency of the text. Feature extraction and target detection are performed on image data. Through computer vision technology, key feature points and target objects in the image are identified, such as detecting faces and vehicles. The audio and video data are converted into a unified processing format for subsequent analysis and processing. A multi-dimensional feature vector is constructed based on the standardized processing results. Multidimensional feature vectors are high-dimensional representations of data, which contain various attributes and features of the data. In order to reduce the dimension and complexity of the data, feature reduction is performed on the multidimensional feature vector to obtain feature descriptors. Feature reduction can be achieved through methods such as principal component analysis, which compresses high-dimensional feature vectors into low-dimensional representations while retaining as much information as possible. For example, for image data, the original high-dimensional pixel features are compressed into low-dimensional main components through principal component analysis. Cluster analysis and anomaly detection are performed on feature descriptors. Cluster analysis is to classify similar data points into one category to form the distribution characteristics of the data; anomaly detection is to identify those abnormal data points that are different from most data points. Through these analyses, the overall distribution of the data and potential anomalies can be understood. For example, for a set of sensor data, cluster analysis can identify data in normal working conditions, while anomaly detection can identify data in fault conditions. According to the data distribution characteristics and anomaly markers, the input data is adaptively sampled and noise filtered to obtain optimized data samples. Adaptive sampling is to dynamically adjust the sampling rate according to the distribution and importance of the data, thereby reducing the amount of data while ensuring data quality; noise filtering is to remove random noise in the data through algorithms to improve data quality. Perform time series analysis and spatial correlation calculation on the optimized data samples. Time series analysis is to identify the law of data change over time, such as periodicity, trend, etc.; spatial correlation calculation is to identify the spatial correlation of data, such as the relationship between geographical locations. Based on these analyses, a description of spatiotemporal characteristics is obtained. Based on the description of spatiotemporal characteristics, a data dependency graph is constructed to show the dependency relationship and transmission path between data. Topological sorting and path analysis are performed on the data dependency graph to obtain a data processing priority strategy.Topological sorting is to determine the order of data processing and ensure that dependencies are handled correctly; path analysis is to identify the key path of data processing and optimize processing efficiency. Based on the data processing priority strategy, the input data is divided into blocks and hashed to obtain a set of data blocks. Blocking is to divide data into multiple small blocks for parallel processing and transmission; hash coding is to generate a unique identifier for each data block to ensure the integrity and uniqueness of the data. For example, hash coding can be generated by the SHA-256 algorithm:. ; in, It is a data block The hash value of the data block. This hash value is used as the unique identifier of the data block for data verification and search. Metadata extraction and semantic annotation are performed on the data block set to obtain a metadata structure containing data attributes and processing tags. Metadata includes information such as the source, format, and processing history of the data. Semantic annotation is to add explanations and labels to the data to facilitate subsequent retrieval and analysis. For example, the metadata of an image data block can include the shooting time, location, content description, etc. of the image.

[0026] In a specific embodiment, the process of executing step S103 may specifically include the following steps: (1) Preliminary screening of the coding rule base based on the metadata structure to obtain a set of candidate rules; (2) Perform weighted scoring on the candidate rule sets to obtain a rule ranking list, and select the rule combination with the highest score based on the rule ranking list. Perform compatibility analysis and conflict detection on the rule combination to obtain the optimized rule chain. (3) Generate a rule decision structure based on the optimized rule chain, perform parameter sensitivity analysis on the rule decision structure, and obtain a parameter adjustment strategy; (4) Dynamically adjust the parameter adjustment strategy and select an adaptive initial encryption scheme from the encryption algorithm library to generate the corresponding key information; (5) Conduct security strength assessment and performance testing on key information, obtain test results, and generate a target encryption scheme based on the test results; (6) Integrate and encapsulate the rule decision structure, key information, and target encryption scheme to generate a configuration object containing the encoding algorithm and key information.

[0027] Specifically, the rules of the coding rule base are preliminarily screened according to the metadata structure to obtain a set of candidate rules. The metadata structure contains various attributes of the input data, such as data type, size, importance, and security requirements. By analyzing the metadata structure, the encoding algorithms, encryption schemes, and mapping rules that match these attributes are screened from the rule base. For example, for a data packet involving a video stream, the preliminarily screening may include video compression algorithms (such as H.264), encryption schemes (such as AES), and mapping rules (such as color conversion from YUV to RGB). The candidate rule set is weighted and scored to determine the priority of each rule. Based on the rule sorting list, the rule combination with the highest score is selected for compatibility analysis and conflict detection. Compatibility analysis is to ensure that the selected rules can work together without conflicts. For example, some encryption schemes may be incompatible with specific compression algorithms, or some mapping rules may be invalid for certain data types. Through conflict detection, these incompatible combinations are identified and excluded to obtain an optimized rule chain. Based on the optimized rule chain, a rule decision structure is generated. This structure describes the execution order and parameter configuration of each rule. In order to ensure the effectiveness of the rule decision structure in actual applications, parameter sensitivity analysis is performed to determine which parameters have the greatest impact on system performance and security, thereby guiding subsequent parameter adjustments. For example, for a video compression algorithm, analyze the impact of parameters such as key frame interval and compression ratio on encoding efficiency and quality. On this basis, dynamically adjust the parameter adjustment strategy, select an adapted initial encryption scheme from the encryption algorithm library, and generate the corresponding key information. For example, after parameter sensitivity analysis, determine the appropriate AES encryption scheme and the corresponding key length. The generated key information includes the key itself and related encryption parameters. Perform security strength assessment and performance testing on the key information. Security strength assessment is to evaluate the key's anti-cracking ability through mathematical analysis and simulated attacks; performance testing is to evaluate the operating efficiency of the encryption algorithm on the target system through actual operation tests. For example, by using AES to encrypt a piece of video data, measure its encryption and decryption time overhead, and evaluate its performance in actual applications. Generate a target encryption scheme based on the results of security strength assessment and performance testing. If the test results show that the current encryption scheme does not meet the requirements in terms of security or performance, optimize the scheme by adjusting the key length or changing the encryption algorithm. Finally, select a target encryption scheme that balances security and performance. The rule decision structure, key information and target encryption scheme are integrated and encapsulated to generate a configuration object containing the encoding algorithm and key information. The configuration object contains all the necessary information to guide the dynamic coding system to process and protect the input data. The configuration object not only includes the selection of encoding and encryption algorithms, but also includes their parameter configuration and execution order, ensuring that data can be processed efficiently and securely in different application scenarios.

[0028] In a specific embodiment, the process of executing step S104 may specifically include the following steps: (1) Adaptively divide the input data into blocks according to the configuration object to obtain multiple data sub-blocks; (2) Perform Fourier transform and wavelet transform on each data sub-block to obtain feature representation, and select the optimal transformation basis for sparse representation based on the feature representation to obtain the compressed data structure; (3) Perform multiple rounds of permutation and diffusion operations on the compressed data structure to obtain preliminary encrypted data; (4) Generate a pseudo-random sequence based on the key information in the configuration object, and perform an XOR operation on the preliminary encrypted data to obtain enhanced encrypted data; (5) performing spatial mapping and color transformation on the enhanced encrypted data according to the mapping rule of the matching code generator to obtain first coded data adapted to the display terminal; (6) performing a reversible watermark embedding on the first coded data to obtain second coded data with hidden information, and performing entropy coding and redundancy coding on the second coded data with hidden information based on the coding algorithm in the configuration object to obtain compressed coded data; (7) Creating initial decoding information, which includes transformation parameters, encryption keys, mapping rules, and encoding methods; (8) Digitally sign the initial decoding information to obtain authenticated decoding information, and package the compressed encoded data and the authenticated decoding information, add a checksum and version information, and obtain an encoded data packet containing the encoded data and the decoding information.

[0029] Specifically, according to the configuration object, the input data is adaptively divided into blocks to obtain multiple data sub-blocks. Adaptive block division divides the data into blocks of appropriate size according to the characteristics of the data and the block division strategy. For example, when processing a video stream, the video is divided into multiple sub-blocks according to the changes in the scene and the complexity of the frame. For static scenes, larger blocks can be selected, while for scenes with drastic dynamic changes, smaller blocks can be selected. Fourier transform and wavelet transform are performed on each data sub-block to obtain a feature representation. The Fourier transform converts the data from the time domain to the frequency domain to reveal its frequency components, while the wavelet transform provides a multi-resolution analysis with both time domain and frequency domain information. These two transforms can extract different features of the data. The Fourier transform can be expressed as: ; in, is the value in the frequency domain, is the data in the time domain, is the number of data points, is a natural constant. Wavelet transform can be expressed as: ; in, are the wavelet coefficients, is the mother wavelet, and are scaling and translation parameters. According to the feature representation, the optimal transformation basis is selected for sparse representation to compress the data structure. For example, for an image, edge features are extracted by wavelet transform, and appropriate transformation basis is selected for sparse representation of these features, which significantly reduces the amount of data. The compressed data structure is subjected to multiple rounds of permutation and diffusion operations to obtain preliminary encrypted data. The permutation operation increases the complexity of the data by disrupting its position, while the diffusion operation enhances the encryption effect through the dependency between data. After multiple rounds of permutation and diffusion, preliminary encrypted data is obtained. Based on the key information in the configuration object, a pseudo-random sequence is generated, and an XOR operation is performed on the preliminary encrypted data to obtain enhanced encrypted data. The pseudo-random sequence generator uses the key information to generate a pseudo-random sequence r with the same length as the preliminary encrypted data. The preliminary encrypted data XOR operation with a pseudo-random sequence: ; in, It is enhanced encrypted data. The unpredictability of the pseudo-random sequence makes the encrypted data more difficult to crack. According to the mapping rules of the matching code generator, the enhanced encrypted data is spatially mapped and color transformed to obtain the first encoded data adapted to the display terminal. The mapping rules convert the data into a format suitable for display according to the characteristics of the display terminal. For example, for image data, the YUV format is converted into RGB format through color transformation to meet the needs of the display terminal. The first encoded data is reversibly watermarked to obtain second encoded data with hidden information. Reversible watermarking technology not only embeds additional information (such as copyright information or authentication logo) in the data, but also can completely restore the original data when needed. Assume that the first encoded data is , after embedding the watermark w, the second encoded data is obtained: ; in, is a parameter that controls the strength of the watermark. Based on the encoding algorithm in the configuration object, the second encoded data with hidden information is entropy encoded and redundantly encoded to obtain compressed encoded data. Entropy encoding (such as Huffman coding) compresses data through the statistical characteristics of data, while redundant encoding increases the reliability of data. For example, using Huffman coding, common data patterns can be represented by shorter codes, while uncommon data patterns can be represented by longer codes, thereby reducing the overall data volume. Create initial decoding information, which contains transformation parameters, encryption keys, mapping rules, and encoding methods. In order to verify the integrity and authenticity of the decoded information, the initial decoded information is digitally signed. Digital signatures generate a signature through encryption technology, and the receiver can use the public key to verify the authenticity of the signature. Pack the compressed encoded data and the authenticated decoded information, add checksums and version information, and obtain an encoded data packet containing the encoded data and the decoded information. The checksum is used to detect errors during data transmission, and the version information helps the receiver identify the format and processing method of the data packet.

[0030] In a specific embodiment, the process of executing step S105 may specifically include the following steps: (1) Analyze the data structure of the coded data packets and stratify them according to their semantics and importance to obtain a multi-layer data structure; (2) Based on the multi-layer data structure, the encoded data packet is unevenly fragmented to obtain multiple original data fragments; (3) Generate a unique shard identifier based on each original data shard, and build a dependency graph between each original data shard to obtain a shard set with topological information; (4) Shuffle and rearrange the shard set with topological information to obtain a random shard sequence, and dynamically generate a key for each original data shard in the random shard sequence to obtain a shard-key correspondence table; (5) According to the shard-key correspondence table, each original data shard in the random shard sequence is encrypted twice to obtain multiple encrypted data shards.

[0031] Specifically, the data structure of the encoded data packet is analyzed, and it is layered according to its semantics and importance to obtain a multi-layer data structure. In this process, the composition of the data packet is first understood, and its semantics and importance are analyzed. The encoded data packet can contain a variety of information, such as source address, destination address, timestamp, data load, etc. According to the different uses and importance of this information, the data packet is decomposed into multiple layers, such as network layer, transport layer, application layer, etc. Based on the multi-layer data structure, the encoded data packet is unevenly fragmented to more finely control the distribution and processing efficiency of the data. Uneven fragmentation refers to dividing the data packet into fragments of different sizes according to the data characteristics and importance of each layer. For example, for important control information, it is divided into smaller fragments, and for large-capacity data information, it is divided into larger fragments. Assume that the length of each layer of data in the data packet is , then the total data length for: .in, Indicates The total data length Split into Uneven sharding , whose lengths are Generate a unique shard identifier for each original data shard, and build a dependency graph between each original data shard to obtain a shard set with topology information. The shard identifier can be a unique value or string to identify each shard. In this process, consider the dependency between each shard. For example, if the shard Depends on sharding , then in the dependency graph, the node Point to Node . The resulting shard set has a clear topological structure and can accurately describe the dependencies between shards. In order to enhance the security of the data packet, the shard set with topological information is shuffled and rearranged to obtain a random shard sequence. The purpose of shuffling and rearranging is to disrupt the original order of the shards, so that even if the shards are intercepted, it is difficult to reconstruct the original data packet. During the shuffling and rearrangement, dynamic key generation is performed for each original data shard in the random shard sequence. Dynamic key generation refers to generating a unique encryption key for each shard according to certain algorithms and rules. Assume that a simple dynamic key generation algorithm is used: ; in, Represents fragmentation The encryption key, represents a secure hash function, represents the exclusive OR operation, Represents a pre-shared key seed. In this way, a shard-key correspondence table is obtained, and each shard corresponds to a unique encryption key. According to the shard-key correspondence table, each original data shard in the random shard sequence is encrypted twice to obtain multiple encrypted data shards. For example, suppose there is a data packet containing the following information: source address, destination address, timestamp, and data payload. According to the different importance of this information, the data packet is divided into three layers: network layer, transport layer, and application layer. Assume that the data length of each layer is 20 bytes, 40 bytes, and 100 bytes, respectively, and the total data length is 160 bytes. The total data length is divided into five uneven shards, which are 20 bytes, 30 bytes, 50 bytes, 30 bytes, and 30 bytes, respectively. Generate a unique identifier for each shard, and build a dependency graph based on the dependencies between them. For example, shard 1 and shard 2 have no dependency, shard 3 depends on shard 1, shard 4 depends on shard 2, and shard 5 depends on shard 3 and shard 4. Shuffle and rearrange the shard set to obtain a random shard sequence. Assume that the shuffled order is shard 4, shard 2, shard 1, shard 5, and shard 3. Generate dynamic keys for each shard and encrypt the shards twice based on these keys. Finally, multiple encrypted data shards are obtained, each with a unique encryption key and random order.

[0032] In a specific embodiment, the process of executing step S106 may specifically include the following steps: (1) Evaluate the transmission priority of multiple encrypted data fragments to obtain a priority transmission queue, and perform real-time detection and evaluation of the network environment based on the priority transmission queue to generate a multi-path transmission solution; (2) Based on the multi-path transmission scheme, network protocol encapsulation and transmission encryption are performed on each encrypted data slice to obtain an encrypted data stream for distributed transmission; (3) In the display terminal, the encrypted data stream of distributed transmission is received and decapsulated and integrity verified to obtain a valid set of encrypted data fragments; (4) Sort and detect missing data in the valid encrypted data shard set to obtain a complete encrypted data shard sequence; (5) Reorganize and splice the complete encrypted data fragment sequence to obtain the data packet to be decrypted, and perform multi-layer decryption on the data packet to be decrypted to obtain the encoded data and decoding information; (6) Based on the algorithm parameters and key in the decoding information, the encoded data is decoded to obtain the input data; (7) Perform format conversion and rendering optimization on the input data, and perform color correction and resolution adjustment according to the hardware parameters and software configuration parameters of the display terminal to obtain display data that is suitable for the display terminal; (8) The display data of the adapted display terminal is transmitted to the graphics processing unit of the display terminal, and the graphics processing unit performs image synthesis and display buffering, and presents the decoded content on the display terminal.

[0033] Specifically, the importance and urgency of multiple encrypted data slices are analyzed to determine their priority in transmission. An evaluation model based on slice characteristics and network conditions is adopted. By analyzing the size, importance and dependency of each slice with other slices, the transmission priority of each slice is calculated. Assume that the priority of each slice is , calculated by the following formula: ; in, Represents fragmentation The priority of Represents fragmentation The size of Represents fragmentation The importance weight of Represents fragmentation The dependency weight of is the weight coefficient, which is used to adjust the influence of various factors in the priority calculation. After obtaining the priority transmission queue, the network environment is detected and evaluated in real time according to the queue to generate a multi-path transmission plan. By real-time detection of available paths in the current network environment, such as bandwidth, delay, packet loss rate and other parameters, the best path is selected for transmission. Assume that there are Available paths, define the path The transmission cost is , and its calculation formula is: ; in, Indicates the path The transmission cost, Indicates the path bandwidth, Indicates the path The delay, Indicates the path The packet loss rate, is a weight coefficient used to adjust the influence of various factors in the calculation of transmission cost. By comparing the transmission costs of different paths, the optimal path is selected for the transmission of data slices. Based on the multi-path transmission scheme, each encrypted data slice is encapsulated and encrypted for transmission to obtain a distributed transmitted encrypted data stream. In this process, each data slice is encapsulated into a data packet that complies with the network protocol, such as a TCP or UDP packet, and is encrypted for transmission to ensure the security of the data during transmission. For example, TLS (Transport Layer Security Protocol) is used to encrypt the data to protect the data from being stolen or tampered with. In the display terminal, the encrypted data stream of distributed transmission is received, and decapsulation and integrity verification are performed to obtain a valid encrypted data slice set. The decapsulation process includes parsing the network protocol header, extracting the original data slice, and checking whether the data has been tampered with during transmission through integrity verification. Integrity verification can be achieved through a checksum or hash function, such as SHA-256. In this way, it is ensured that the received data is complete and correct. After sorting and missing detection of the valid encrypted data slice set, a complete encrypted data slice sequence is obtained. The sorting process restores the fragments to their original order based on their identifiers, and missing detection determines whether any fragments are lost during transmission by checking the continuity of the fragment identifiers. If missing fragments are detected, the sender is requested to resend these fragments to ensure data integrity. The complete encrypted data fragment sequence is reassembled and spliced ​​to obtain the data packet to be decrypted, and the data packet to be decrypted is decrypted in multiple layers to restore the original encoded data and decoding information. Assuming that a symmetric encryption algorithm (such as AES) is used for encryption, the decryption process is as follows: ; in, Indicates the decrypted data fragment. Indicates the decryption operation, Represents fragmentation The encryption key is used. By decrypting all the slices, the complete encoded data and decoding information are obtained. Based on the algorithm parameters and keys in the decoding information, the encoded data is decoded to obtain the input data. Decoding refers to restoring the encoded data to the original input data according to the predetermined algorithm and key. The input data is format converted and rendered, and color correction and resolution adjustment are performed according to the hardware parameters and software configuration parameters of the display terminal to obtain display data adapted to the display terminal. Assuming that the input data is image data, the following formula is used for color correction: ; in, represents the corrected color value, Represents the original color value, and It is a correction parameter, which is determined according to the hardware and software configuration of the display terminal. The display data of the adapted display terminal is transmitted to the graphics processing unit of the display terminal, and the image synthesis and display buffering are performed by the graphics processing unit, and the decoded content is presented on the display terminal.

[0034] The above describes the method for dynamically matching code to control the display terminal in the embodiment of the present application. The following describes the device for dynamically matching code to control the display terminal in the embodiment of the present application. Figure 2 In the embodiment of the present application, an embodiment of the device for dynamically matching code to control the display terminal includes: The construction module 201 is used to integrate and process the parameters of the code matching rule library, the code matching generator and the display terminal to build a dynamic code matching system; The acquisition module 202 is used to acquire input data of the display terminal based on the dynamic code matching system, and pre-process and analyze the input data to obtain a metadata structure including data attributes and processing marks; The matching module 203 is used to call the coding rule library to perform coding rule matching and parameter adjustment on the metadata structure to obtain a configuration object including the coding algorithm and key information; The processing module 204 is used to segment, transform, encrypt and map the input data based on the configuration object and the code generator to obtain a coded data packet containing coded data and decoding information; The encryption module 205 is used to perform fragmentation and secondary encryption processing on the encoded data packet to obtain multiple encrypted data fragments; The reassembly module 206 is used to perform multi-path transmission and reassembly on multiple encrypted data slices to obtain reassembled data, and decode and present the reassembled data on the display terminal.

[0035] Through the cooperation of the above components, by integrating the coding rule library, coding generator and display terminal parameters, the dynamic call and update of coding rules are realized, the input data is analyzed and processed in multiple dimensions, and a metadata structure containing rich semantic information is generated. Based on the metadata structure, rule matching and parameter adjustment are performed to realize the dynamic selection of encoding algorithms and encryption schemes. Through multiple processing such as segmentation, transformation, encryption and mapping, the security and transmission efficiency of data are improved, and the reversibility of data is guaranteed. The uneven sharding and dynamic key encryption of the encoded data packets enhance the security of data transmission, realize the priority transmission and distributed transmission of data shards, improve the transmission efficiency and anti-interference ability, and ensure the integrity of data. Decoding and rendering optimization are carried out according to the characteristics of the display terminal to ensure the best display effect of the decoded data on different terminals. By dynamically adjusting the encoding algorithm and parameters, as well as the intelligent sharding and transmission strategy, efficient utilization of computing resources and network bandwidth is achieved, thereby realizing the security and flexible control of the content of the display terminal.

[0036] The present application also provides a device for dynamically matching code to control a display terminal, the device for dynamically matching code to control a display terminal includes a memory and a processor, the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the method for dynamically matching code to control a display terminal in the above-mentioned embodiments.

[0037] The present application also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the method for dynamically matching codes to control a display terminal.

[0038] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0039] If the integrated unit 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 application is essentially or the part that contributes to the prior art or all or 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 to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0040] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for dynamically matching codes to control a display terminal, characterized in that: The method comprises: Integrate and process the parameters of the coding rule library, coding generator and display terminal to build a dynamic coding system; Based on the dynamic code matching system, the input data of the display terminal is acquired, and the input data is preprocessed and analyzed to obtain a metadata structure including data attributes and processing marks; Calling the coding rule library to perform coding rule matching and parameter adjustment on the metadata structure to obtain a configuration object including coding algorithm and key information; Based on the configuration object and the matching code generator, the input data is segmented, transformed, encrypted and mapped to obtain a coded data packet containing coded data and decoding information; Slicing and re-encrypting the encoded data packet to obtain a plurality of encrypted data slices; The plurality of encrypted data fragments are multi-path transmitted and reassembled to obtain reassembled data, and the reassembled data is decoded and presented on the display terminal.

2. The method for dynamically matching code to control display terminal according to claim 1, characterized in that: The said integrating and processing the parameters of the code matching rule library, the code matching generator and the display terminal to construct a dynamic code matching system includes: Classify and organize multiple encoding algorithms, multiple encryption schemes and mapping rules to obtain a coding rule base, and perform rule priority sorting and association analysis on the coding rule base to obtain a coding rule network; Indexing and associative analysis are performed on the coding rule network to obtain a rule index tree, and initialization settings are performed on the initial generator according to the rule index tree to obtain a coding engine that can dynamically call rules; The hardware parameters and software configuration parameters of the display terminal are collected and standardized to obtain a standardized terminal parameter set, and the coding engine is optimized and adapted according to the standardized terminal parameter set to obtain a coding generator; Cross-validating the code matching rule base and the code matching generator to obtain a rule-generator matching matrix, and dynamically updating the code matching rule base according to the rule-generator matching matrix to obtain an adaptive rule updating strategy; The adaptive rule update strategy and the matching code generator are integrated and globally optimized to construct a dynamic matching code system.

3. The method for dynamically matching code to control display terminal according to claim 1, characterized in that: The dynamic code matching system obtains the input data of the display terminal, and pre-processes and analyzes the input data to obtain a metadata structure including data attributes and processing marks, including: Based on the dynamic code matching system, multi-threaded monitoring is performed on the input interface of the display terminal to obtain input data; Classify the input data to obtain multiple typed data sets, perform word segmentation and semantic analysis on the text data in the typed data sets, perform feature extraction and target detection on the image data in the typed data sets, perform codec format conversion on the audio and video data in the typed data sets, and obtain standardized processing results; Constructing a multidimensional feature vector according to the standardization processing result, and performing feature dimension reduction on the multidimensional feature vector to obtain a feature descriptor; Performing cluster analysis and anomaly detection on the feature descriptors to obtain data distribution characteristics and potential anomaly markers, and performing adaptive sampling and noise filtering on the input data according to the data distribution characteristics and the anomaly markers to obtain optimized data samples; Performing time series analysis and spatial correlation calculation on the optimized data samples to obtain a spatiotemporal feature description, constructing a data dependency graph based on the spatiotemporal feature description, and performing topological sorting and path analysis on the data dependency graph to obtain a data processing priority strategy; The input data is divided into blocks and hash-encoded based on the data processing priority strategy to obtain a data block set, and metadata extraction and semantic annotation are performed on the data block set to obtain a metadata structure including data attributes and processing tags.

4. The method for dynamically matching code to control display terminal according to claim 1, characterized in that: The calling of the coding rule library to perform coding rule matching and parameter adjustment on the metadata structure to obtain a configuration object containing a coding algorithm and key information includes: Performing a preliminary screening of the coding rule base according to the metadata structure to obtain a candidate rule set; Performing weighted scoring on the candidate rule sets to obtain a rule ranking list, selecting a rule combination with the highest score based on the rule ranking list, performing compatibility analysis and conflict detection on the rule combination to obtain an optimized rule chain; Generate a rule decision structure according to the optimized rule chain, and perform parameter sensitivity analysis on the rule decision structure to obtain a parameter adjustment strategy; Dynamically adjust the parameter adjustment strategy and select an adaptive initial encryption scheme from the encryption algorithm library to generate corresponding key information; Performing security strength assessment and performance testing on the key information to obtain test results, and generating a target encryption scheme based on the test results; The rule decision structure, the key information and the target encryption scheme are integrated and packaged to generate a configuration object including an encoding algorithm and key information.

5. The method for dynamically matching code to control display terminal according to claim 4, characterized in that: The input data is segmented, transformed, encrypted and mapped based on the configuration object and the code generator to obtain a coded data packet containing coded data and decoding information, including: According to the configuration object, adaptively divide the input data into blocks to obtain a plurality of data sub-blocks; Performing Fourier transform and wavelet transform on each data sub-block to obtain feature representation, and selecting an optimal transformation basis for sparse representation according to the feature representation to obtain a compressed data structure; Performing multiple rounds of permutation and diffusion operations on the compressed data structure to obtain preliminary encrypted data; Based on the key information in the configuration object, a pseudo-random sequence is generated, and an XOR operation is performed on the preliminary encrypted data to obtain enhanced encrypted data; According to the mapping rule of the matching code generator, the enhanced encrypted data is spatially mapped and color transformed to obtain first coded data adapted to the display terminal; Performing a reversible watermark embedding on the first coded data to obtain second coded data with hidden information, and performing entropy coding and redundancy coding on the second coded data with hidden information based on the coding algorithm in the configuration object to obtain compressed coded data; Creating initial decoding information, wherein the initial decoding information includes transformation parameters, encryption keys, mapping rules, and encoding methods; The initial decoding information is digitally signed to obtain authenticated decoding information, and the compressed coded data and the authenticated decoding information are packaged, and a checksum and version information are added to obtain a coded data packet containing the coded data and the decoding information.

6. The method for dynamically matching code to control display terminal according to claim 1, characterized in that: The step of slicing and re-encrypting the encoded data packet to obtain a plurality of encrypted data slices includes: Performing data structure analysis on the coded data packets and layering them according to the semantics and importance of the coded data packets to obtain a multi-layer data structure; Based on the multi-layer data structure, the encoded data packet is unevenly fragmented to obtain a plurality of original data fragments; Generate a unique shard identifier based on each original data shard, and build a dependency graph between each original data shard to obtain a shard set with topology information; Shuffling and rearranging the shard set with topology information to obtain a random shard sequence, and dynamically generating a key for each original data shard in the random shard sequence to obtain a shard-key correspondence table; According to the shard-key correspondence table, each original data shard in the random shard sequence is encrypted twice to obtain multiple encrypted data shards.

7. The method for dynamically matching code to control display terminal according to claim 1, characterized in that: The multi-path transmission and reorganization of the plurality of encrypted data fragments to obtain reorganized data, and decoding and presenting the reorganized data on the display terminal, comprises: Performing transmission priority evaluation on the multiple encrypted data slices to obtain a priority transmission queue, and performing real-time detection and evaluation of the network environment according to the priority transmission queue to generate a multi-path transmission solution; Based on the multi-path transmission scheme, network protocol encapsulation and transmission encryption are performed on each encrypted data slice to obtain an encrypted data stream for distributed transmission; In the display terminal, the distributed transmitted encrypted data stream is received and decapsulated and integrity verified to obtain a valid encrypted data fragment set; Sorting and missing detection are performed on the valid encrypted data shard set to obtain a complete encrypted data shard sequence; Recombining and splicing the complete encrypted data fragment sequence to obtain a data packet to be decrypted, and performing multi-layer decryption on the data packet to be decrypted to obtain encoded data and decoding information; Based on the algorithm parameters and the key in the decoding information, the encoded data is decoded to obtain the input data; Performing format conversion and rendering optimization on the input data, and performing color correction and resolution adjustment according to the hardware parameters and software configuration parameters of the display terminal to obtain display data adapted to the display terminal; The display data adapted to the display terminal is transmitted to the graphics processing unit of the display terminal, and the graphics processing unit performs image synthesis and display buffering, and the decoded content is presented on the display terminal.

8. A device for dynamically matching codes to control display terminals, characterized in that: A method for executing a dynamic code matching control display terminal according to any one of claims 1 to 7, the device comprising: The construction module is used to integrate and process the parameters of the coding rule base, coding generator and display terminal to build a dynamic coding system; An acquisition module, used for acquiring input data of the display terminal based on the dynamic coding system, and preprocessing and analyzing the input data to obtain a metadata structure including data attributes and processing marks; A matching module, used to call the coding rule library to perform coding rule matching and parameter adjustment on the metadata structure to obtain a configuration object including a coding algorithm and key information; A processing module, used to segment, transform, encrypt and map the input data based on the configuration object and the matching code generator to obtain a coded data packet containing coded data and decoding information; An encryption module, used for performing fragmentation and secondary encryption processing on the encoded data packet to obtain a plurality of encrypted data fragments; The reassembly module is used to perform multi-path transmission and reassembly on the multiple encrypted data fragments to obtain reassembled data, and decode and present the reassembled data on the display terminal.

9. A device for dynamically matching code to control display terminal, characterized in that: The device of the dynamic code matching control display terminal includes: a memory and at least one processor, wherein the memory stores instructions; The at least one processor calls the instruction in the memory to enable the device of the dynamic coding control display terminal to execute the method for dynamic coding control display terminal according to any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the method for dynamically matching codes to control a display terminal according to any one of claims 1 to 7 is implemented.

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