Data line dynamic transmission method and system based on data security

Abstract

The invention discloses a dynamic transmission method and system of a data line based on data security, relates to the technical field of data security, and determines a scene where the data line is located based on tracing of the data line. According to the scene, the data security mechanism of the data security module and the previous transmission event of the data line, the transmission management and control mechanism of the data line is determined, and the data security means of the data line for the data is determined in combination with the data type of the data, so that the accuracy of the data security means of the data line for the data is improved. Marking a plurality of data encryption nodes in the data line, and determining a multi-point collaborative management and control system according to the position of each data encryption node, the corresponding data distribution event and the data security means; the transmission progress of the data is determined according to dynamic identification of the multi-point collaborative management and control system, the data transmission mode of the data line is determined by combining the data type of the data and the corresponding data transmission requirement, and online safety management and control and transmission efficiency of the data are compatible.

Description

A dynamic transmission method and system based on data security data cables Technical Field

[0001] This invention relates to the field of data security technology, and in particular to a dynamic transmission method and system based on a data security data line. Background Technology

[0002] With the rapid development of information technology, data cables, as a key physical medium for data interaction and energy transfer between electronic devices, have expanded their application scenarios from simple consumer electronics to complex fields such as industrial control, security monitoring, medical equipment, and the Internet of Things. In these application scenarios, data cables not only need to ensure high-speed data throughput, but also the security and integrity of the transmitted content. Especially when carrying sensitive information or critical control commands, the transmission security capabilities of data cables are particularly important.

[0003] Existing technologies often treat data cables as simple physical transmission channels, ignoring the differentiated risks associated with data cables in various connection scenarios and transmission environments. Traditional security measures typically employ static, uniform configuration strategies, which cannot dynamically adapt to the port topology, hardware configuration, and real-time transmission environment of the data cable. This makes it difficult to distinguish the real-time data type and match the corresponding scenario risk level, resulting in low accuracy of data security measures for that data and an inability to achieve both online security management and efficient transmission. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art. This invention provides a dynamic transmission method and system based on data security data lines.

[0005] This invention provides a dynamic transmission method for a data line based on data security, comprising: transmitting data via the data line, wherein a corresponding data security module is configured during data transmission; the data security module identifies the data and determines the corresponding data type based on the identification result and the data signal output by the data line; determining the scenario where the data line is located based on the traceability of the data line; determining the transmission control mechanism of the data line based on the scenario, the data security mechanism of the data security module, and the data line's past transmission events; determining the data security measures for the data line based on the data type; marking the data transmission path of the data line and marking multiple data encryption nodes in the data line; determining a multi-point collaborative control system based on the location of each data encryption node, the corresponding data diversion event, and the data security measures; determining the data transmission progress based on the dynamic identification of the multi-point collaborative control system; determining the data transmission mode of the data line based on the data type and the corresponding data transmission requirements; and optimizing the dynamic transmission process of the data line.

[0006] This invention provides a dynamic transmission system for a data cable based on data security. This system is applied to the aforementioned dynamic transmission method for a data cable based on data security. The system includes: a data type module for transmitting data via the data cable, configured with a corresponding data security module during data transmission. This data security module identifies the data and determines the corresponding data type based on the identification result and the data signal output by the data cable; and a data security module for determining the scenario where the data cable is located based on its traceability, and determining the scenario, the data security mechanism of the data security module, and... The data line's past transmission events determine its transmission control mechanism, and the data security measures for the data are determined based on the data type. A multi-point collaborative control system module marks the data transmission path on the data line and identifies multiple data encryption nodes. The multi-point collaborative control system is determined based on the location of each encryption node, the corresponding data diversion events, and the data security measures. A dynamic transmission module, within this multi-point collaborative control system, determines the data transmission progress based on the system's dynamic identification, and, combined with the data type and corresponding data transmission requirements, determines the data transmission mode and optimizes the dynamic transmission process.

[0007] Compared with the prior art, the beneficial effects of the present invention are: (1) The data line transmits data and is equipped with a corresponding data security module during the data transmission process. At this time, the data security module identifies the data and determines the corresponding data type based on the identification result and the data signal output by the data line; the scene where the data line is located is determined based on the traceability of the data line, and the transmission control mechanism of the data line is determined according to the scene, the data security mechanism of the data security module and the previous transmission events of the data line, and the data security measures of the data line for the data are determined in combination with the data type, thereby realizing the data line's security control of the data and fully considering the data line's transmission control mechanism and the data type, thus improving the accuracy of the data line's data security measures for the data.

[0008] (2) Mark the data transmission path on the data line and mark multiple data encryption nodes in the data line. Determine the multi-point collaborative management and control system based on the location of each data encryption node, the corresponding data diversion event and data security measures. In the multi-point collaborative management and control system, determine the data transmission progress based on the dynamic identification of the multi-point collaborative management and control system. Combine the data type and corresponding data transmission requirements to determine the data transmission mode of the data line and optimize the dynamic transmission process of the data line. The multi-point collaborative management and control system is introduced to perform encryption management and control on multiple data encryption nodes of the data line and to deeply manage the data transmission mode of the data line in order to optimize the dynamic transmission process of the data line and to be compatible with online security management and transmission efficiency of data. Attached Figure Description

[0009] Figure 1 is a flowchart illustrating the dynamic transmission method based on data security data lines in an embodiment of the present invention; Figure 2 is a flowchart illustrating step S11 in the dynamic transmission method based on data security data lines in an embodiment of the present invention; Figure 3 is a flowchart illustrating step S12 in the dynamic transmission method based on data security data lines in an embodiment of the present invention; Figure 4 is a flowchart illustrating step S13 in the dynamic transmission method based on data security data lines in an embodiment of the present invention; Figure 5 is a flowchart illustrating step S14 in the dynamic transmission method based on data security data lines in an embodiment of the present invention; Figure 6 is a schematic diagram illustrating the structural composition of the dynamic transmission system based on data security data lines in an embodiment of the present invention. Detailed Implementation

[0010] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0011] Please refer to Figures 1 to 6. A dynamic transmission method for a data cable based on data security is applied to a data security scenario. The dynamic transmission method for a data cable based on data security includes: Step S11: The data cable transmits data, and a corresponding data security module is configured during the data transmission process. At this time, the data security module identifies the data, and the corresponding identification result and the data signal output by the data cable determine the corresponding data type; Step S12: Based on the tracing of the data cable, the scenario where the data cable is located is determined. Based on the scenario, the data security mechanism of the data security module, and the previous transmission events of the data cable, the transmission control mechanism of the data cable is determined, and the data security measures for the data cable are determined in combination with the data type; Step S13: The transmission path of the data on the data cable is marked, and multiple data encryption nodes are marked in the data cable. A multi-point collaborative control system is determined based on the location of each data encryption node, the corresponding data diversion event, and the data security measures; Step S14: In the multi-point collaborative control system, the transmission progress of the data is determined based on the dynamic identification of the multi-point collaborative control system. The data transmission mode of the data cable is determined in combination with the data type and the corresponding data transmission requirements, and the dynamic transmission process of the data cable is optimized.

[0012] Referring to Figure 2, in step S11, the specific steps are as follows: S111: Real-time monitoring of data transmission via the data line. The data line is equipped with a corresponding data security module. During transmission, the data passes through the data security module, triggering dynamic identification of the data and performing multi-dimensional scanning of the data payload, protocol characteristics, and content to match the corresponding identification results for the data; S112: Acquiring the data signal output by the data line and determining the data attributes by parsing the data signal. Performing multi-level iterations on the data attributes and identification results corresponding to the data, and gradually determining the data type of the data during the iteration process to determine the data type of the data in multiple dimensions.

[0013] In the embodiments of this application, the data transmission of the data line is monitored in real time. The data line is configured with a corresponding data security module. During the transmission process, the data passes through the data security module and triggers the data security module to dynamically identify the data. The data payload, protocol features and content are scanned in multiple dimensions to match the corresponding identification results. The identification results corresponding to the data are introduced.

[0014] At this time, the data security module is embedded in the data line transmission link and captures the bit stream flowing through it in real time through a high sampling rate signal probe. When the frame header or a specific identification field of the data stream enters the module's sensing area, a dynamic identification process is immediately triggered. This process requires extremely low processing latency to ensure that it will not become a transmission bottleneck. Technically, a parallel pipeline processing architecture is adopted to make the monitoring action and data flow synchronized.

[0015] Simultaneously, the data payload, protocol characteristics, and content are scanned in multiple dimensions. The payload is the actual content of the data. The Shannon entropy of the data payload is introduced to determine the randomness of the data. High entropy values ​​usually correspond to encrypted data or compressed video streams, while low entropy values ​​correspond to text or structured instructions. The payload is sliced, and key bit sequences are extracted to form feature vectors for matching known data patterns.

[0016] The system performs in-depth analysis of protocol characteristics, focusing on the encapsulation structure of the data link layer and transport layer; it parses the header fields of data packets to identify the protocol type, encapsulation format, and control flags; furthermore, by identifying "protocol information" (such as proprietary protocol headers of specific vendors and custom padding fields), it can distinguish between standard protocols and proprietary protocols.

[0017] After parsing the payload and protocol, the system performs semantic-level association and identifies key instruction sets or media frame boundaries (such as I-frames and P-frames) in the content through pattern matching algorithms. The multi-dimensional scanning results are then mapped to a predefined security tag library, and a high-confidence recognition result is output.

[0018] Specifically, data cables are currently facing complex application scenarios: simultaneously carrying the mixed transmission tasks of industrial control commands and high-definition surveillance video. These two data types have drastically different transmission requirements—the former requires extremely low latency and high reliability, while the latter requires high bandwidth and allows for a certain degree of frame loss.

[0019] When the data security module of the data line starts real-time monitoring, a high-speed serial bit stream continuously flows into the module buffer; this triggers a dynamic identification process, in which the module strips the mixed data stream frame by frame; regarding the load scanning stage, the system detects obvious load characteristic boundaries in the data stream: for intermittently inserted small-volume data packets, the system measures that their load entropy value is low and exhibits regular byte alignment characteristics, which is consistent with the characteristics of industrial control instructions (such as motor start / stop, position correction instructions) being highly structured and having low redundancy; for continuously throughput large-volume data packets, the system measures that their load entropy value is extremely high and exhibits obvious macroblock segmentation characteristics, which precisely corresponds to the high-density data form of the high-definition monitoring video stream after H.264 / H.265 encoding and compression.

[0020] At the protocol feature parsing level, the data line's security module further confirmed that low-entropy data packets (control commands) were identified as encapsulating a proprietary industrial Ethernet protocol, with their frame headers containing specific device address mappings; while high-entropy data packets (video streams) were identified as encapsulating standard RTP / UDP protocols, with the header timestamp field continuously increasing.

[0021] Based on the above multi-dimensional scanning results, the system enters the final identification result matching stage; the data security module no longer treats all data as indiscriminate bit streams, but outputs accurate identification conclusions: the mixed data stream is decomposed and identified as "high priority - industrial control command" and "normal priority - high-definition video stream", which provides a decisive input basis for the subsequent construction of differentiated transmission control mechanism for the data line, thereby ensuring that critical control commands are not squeezed out by the video stream or congested in mixed transmission high-load scenarios.

[0022] Furthermore, the data signal output by the data line is collected, and the data attributes are determined by analyzing the data signal. The data attributes and recognition results corresponding to the data are iterated at multiple levels, and the data type of the data is gradually determined during the iteration process. This approach determines the data type of the data from multiple dimensions, taking into account the overall consideration of data signal analysis and ensuring the accuracy of data attributes.

[0023] At this time, the system captures the electrical signal characteristics of the data line output terminal through the high-speed signal acquisition unit, including the voltage amplitude of the differential signal, the steepness of the transition edge, the signal jitter, and the transmission timing interval. By analyzing these physical characteristics, the system constructs the "transmission morphology attributes" of the data, such as determining whether the data stream exhibits the characteristics of "continuous high duty cycle" (usually corresponding to large data stream transmission) or "microsecond-level burst pulse" (usually corresponding to signaling or control commands).

[0024] Based on the parsed physical signal characteristics, the system converts the signal waveform into logical attribute labels. This process maps the "voltage and timing" of the physical layer to the "traffic behavior" and "interaction mode" of the transmission layer. For example, periodic short frame signals are mapped to "attributes", and continuous long frame signals are mapped to "streaming media attributes". This step establishes the objective transmission behavior characteristics of the data.

[0025] The system constructs a multi-dimensional state space to associate and match "content recognition results" (such as structured instructions and video frames) with "transmission attributes" (such as burst pulses and continuous streams). If the content recognition result and the transmission attribute are highly consistent (such as being identified as a video stream with the attribute of continuous high bandwidth), the confidence level is increased. If a conflict occurs (such as being identified as text but with the attribute of high bandwidth continuous stream), re-recognition or de-weighting is triggered. As the data stream continues to be input, the system continuously adjusts the confidence level within the time window, replacing low-probability assumptions through multi-level iterations, and finally locking in a unique data type.

[0026] After iterative convergence, the system outputs a final data type containing multi-dimensional tags such as "content semantics", "transmission behavior", and "priority attributes". This is no longer a simple string tag, but a structured feature vector that describes the whole picture of the data, providing accurate input for the subsequent selection of security measures.

[0027] Specifically, the signal acquisition unit of the data line starts working; in response to the current mixed transmission condition, the system captures two distinct physical signal characteristics: one type of signal is a microsecond-level burst pulse sequence with extremely regular signal level jumps and precise periodicity in the frame interval; the other type of signal is a continuous differential signal stream with an extremely high duty cycle and is accompanied by dynamic rate adjustment characteristics that adapt to changes in channel bandwidth.

[0028] Based on this, the system performs data attribute parsing and mapping: for burst pulse sequences, the system defines its attributes as "low latency, high reliability interactive attributes"; for continuous signal streams, the system defines its attributes as "high throughput, jitter-tolerant streaming attributes".

[0029] The system initiates a critical multi-level iterative process to deeply integrate the above attributes with the recognition results: First level iteration: The system matches "interactive attributes" with "industrial control instructions"; the feature vectors of the two are highly overlapping - the content is structured instructions and the transmission behavior is low-latency bursts. Based on this, the system raises the confidence of the data stream to "extremely high" and initially locks it as "real-time control data".

[0030] Second-level iteration: The system processes video stream data; it identifies it as "high-definition surveillance video", but the transmission attributes show that its bandwidth fluctuates at certain times; the iterative algorithm, combined with scenario analysis, determines that this is due to bandwidth oscillation caused by the control command preemption priority during mixed transmission, rather than a misjudgment of data type; the system confirms that it still belongs to "video surveillance data" by correcting the model, and adds a "bandwidth limited" status flag.

[0031] The mixed data streams output from the data cable are precisely separated, with one group identified as "hard real-time industrial control data" and the other as "non-real-time high-definition monitoring video data." This multi-dimensional type determination not only clarifies "what" the data is, but also "how" the data is transmitted, laying a solid logical foundation for implementing differentiated transmission control mechanisms for different data types in subsequent step S12 (such as implementing redundancy correction for control data and frame loss reordering for video data).

[0032] Referring to Figure 3, the specific steps in step S12 are as follows: S121: Trace the data line and determine the port routing route of the data line during the tracing process. Determine the primary scenario of the data line along the port routing route, the corresponding hardware configuration, and the corresponding transmission environment. Combine the timestamp sequence of the data line with the data throughput to perform multi-factor fusion to determine the scenario in which the data line is located; S122: Mark the data security module and determine the corresponding data security library based on the self-identification of the data security module. Determine the corresponding data security mechanism based on the traversal of the data security library. At the same time, collect the past transmission events of the data line, perform multi-factor iteration on the scenario, the data security mechanism of the data security module, and the past transmission events of the data line, and output multiple transmission control factors of the data line in the scenario; S123: Construct the transmission control mechanism of the data line based on the multiple transmission control factors, extract multiple data transmission features, and determine the data security measures of the data line for the data based on the matching of multiple data transmission features and the data type. The data security measures cover privacy protection measures, data error correction measures, and data encryption measures.

[0033] In the embodiments of this application, the data line is traced, and the port routing route of the data line is determined during the tracing process. The primary scenario of the data line is determined along the port routing route, the corresponding hardware configuration, and the corresponding transmission environment. The data line's timestamp sequence and data throughput are combined to perform multi-factor fusion to determine the scenario in which the data line is located. This approach takes into account the overall considerations of the port routing route, the corresponding hardware configuration, and the corresponding transmission environment, ensuring the accuracy of the primary scenario of the data line.

[0034] At this point, hardware topology identification technology is used to trace the physical transmission path of the data signal in reverse or forward. The system reads the physical layer register information inside the data line interface, parses the topology connection relationship of the port, and clarifies the physical link path of the data from the source to the destination. This is not only to confirm the connection status, but also to identify which physical nodes (such as repeaters, switching chips, and bridging controllers) the data passes through during transmission, thereby constructing a physical transmission topology map.

[0035] After clarifying the physical path, the system combines three key parameters to create a preliminary scenario profile: Hardware configuration: Identify the hardware computing power, power supply capacity, and interface specifications (such as USB 3.0 / 3.1 / industrial Ethernet port) of the devices at both ends of the link to determine whether they have high-performance encryption or can only perform lightweight verification; Transmission environment: Assess the current electromagnetic interference intensity, signal-to-noise ratio (SNR), and link stability to determine whether it is in a well-shielded computer room environment or an electromagnetically complex open-air industrial site; Based on the above two, the system initially defines the scenario attributes (such as: highly stable static scenario, highly interference dynamic scenario).

[0036] The initial scenario only reflects static physical attributes. However, by introducing dynamic operational indicators, the scenario can be dynamically corrected: Timestamp sequence analysis: analyzes the distribution pattern of data packet arrival time intervals; periodic distribution usually corresponds to timed collection or heartbeat maintenance, while random burst distribution corresponds to manual operation or event triggering; Data throughput analysis: monitors bit traffic per unit time to determine the link load status (idle, load balanced, overload congestion); the system adopts a weighted fusion algorithm to fit the static physical scenario with dynamic traffic characteristics, eliminating the ambiguity of single-dimensional judgment; after physical tracing and dynamic data fusion, the system outputs a scenario label with high semantic features. This label is no longer a simple location description, but a composite state vector containing "physical link risk level" and "business behavior characteristics".

[0037] Specifically, the system initiates physical tracing of the data line. By reading the configuration descriptor in the data line interface controller, the system parses out that the data line is not connected to a regular PC terminal, but to the downlink port of the industrial field gateway. The system traces the port's routing route and finds that the data flow passes through multiple layers of shielding and signal enhancement relay units inside the data line, and finally merges into the core industrial switching backplane.

[0038] In terms of hardware configuration, the system identifies that both ends of the link are equipped with dedicated high-performance signal processing chips, which support hardware-level data verification and encryption acceleration. In terms of transmission environment, the system detects periodic electromagnetic pulse interference in the line, with the signal-to-noise ratio fluctuating within a certain range. Based on this, the system determines the primary scenario as a "high-interference industrial-grade hybrid link", which is a physical environment with stringent requirements for transmission stability.

[0039] The system incorporates timestamp sequences and throughput to accurately characterize the current business scenario: Timestamp sequence analysis shows that the data packets arriving on the data line exhibit a mixed superposition of "microsecond-level precise cycles" and "random long frame continuity," which matches the "control command + video stream" hybrid transmission characteristics determined in S112, indicating that the system is in a business mode of real-time control and monitoring in parallel; Data throughput analysis shows that the current link bandwidth utilization rate has reached over 75%, approaching a high-load operating state, but no congestion or packet loss has occurred. The system ultimately determines the scenario where the data line is located as a "high-load industrial real-time control and monitoring hybrid scenario." This scenario conclusion indicates that the data line is currently in a critical operating condition with a harsh electromagnetic environment, scarce bandwidth resources, and significant differences in business priorities. This scenario determination result is then input into the subsequent step S122 as an important decision-making basis for formulating transmission control mechanisms and security measures, ensuring that priority can be forcibly preempted when facing control commands, and that the remaining bandwidth can be dynamically adapted when facing video streams.

[0040] Furthermore, data security modules are tagged, and corresponding data security libraries are determined based on the self-identification of the data security modules. The corresponding data security mechanisms are determined based on the traversal of the data security libraries. At the same time, past transmission events of the data line are collected, and multi-factor iteration is performed on the scenario, the data security mechanisms of the data security modules, and the past transmission events of the data line. Multiple transmission control factors of the data line in the scenario are output, which is compatible with the overall consideration of the traversal of the data security libraries and ensures the accuracy of the corresponding data security mechanisms.

[0041] At this point, the activated data security module is uniquely marked to confirm its identity and permission level. Subsequently, the system indexes the module's dedicated "data security library" through an internal mapping table based on the module's hardware ID or logical identifier. This security library is not a general database, but a dedicated resource pool that contains the set of encryption algorithms (such as AES and SM4) supported by the module, a set of verification rules, key management strategies, and contingency plans for handling anomalies.

[0042] The system performs a full or heuristic traversal of the data security database to extract currently available security mechanisms. This process involves not only listing algorithms but also evaluating the applicability of each mechanism in the current environment. For example, it selects lightweight encryption mechanisms suitable for low-latency environments or strong encryption mechanisms suitable for highly sensitive environments. The final security mechanisms will serve as the "capability boundaries" for subsequent control factors.

[0043] The system retrieves historical transmission records of the data line from non-volatile memory or a log server. The key data collection points include: historical transmission error rate, frequency of congestion, records of abnormal attack interception, and the success rate of scheduling strategies under mixed traffic. By extracting the statistical characteristics of these events, a "historical experience vector" is formed to provide a reference benchmark for current decision-making.

[0044] The system constructs a multi-dimensional decision-making model, taking the determined "scenario characteristics," the currently traversed "data security mechanisms," and the historically extracted "past transmission events" as input variables. Simultaneously, a weighted iterative algorithm is used to evaluate the comprehensive effectiveness of different security mechanisms under the current scenario and historical constraints. If historical data shows that a certain encryption algorithm leads to high latency in high-interference scenarios, the weight of this factor is reduced during iteration. After the iteration converges, the system outputs a set of specific "transmission control factors." These factors are no longer abstract strategies but concrete control parameters, such as "transmission priority weight," "encryption strength level," "retransmission timeout threshold," and "bandwidth reservation ratio."

[0045] Specifically, the system marks and identifies the currently active data security module, confirming that the module is a "data cable dedicated industrial-grade security module". Based on the module identifier, the system indexes and loads the corresponding data security library, which is pre-loaded with high-strength encryption algorithms (such as AES-256), lightweight verification algorithms (such as CRC-16 / CCITT), and dynamic encryption encapsulation protocols for streaming media suitable for industrial environments.

[0046] The system performs a security mechanism traversal; considering that the data line is currently under high load, the system excludes the computationally expensive full-coverage deep encryption mechanism and instead selects two highly adaptable mechanisms, "differential signal encryption" and "critical field verification", thus initially defining the scope of security measures.

[0047] The system collects past transmission events of the data line; historical logs show that in similar mixed transmission tasks in the past, when the data line encountered electromagnetic interference, the use of complex encryption caused the control command delay to exceed the standard; at the same time, historical data also recorded the pattern that when the video stream occupied more than 80% of the bandwidth, the control command packet loss rate increased significantly.

[0048] The system integrates the sensitivity of "high-interference industrial scenarios" to bit error rate, the impact of "data security mechanisms" on latency, and lessons learned from "historical transmission events" for calculation. Iteration process one: For industrial control commands, based on historical lessons, the system determines that high-latency complex encryption mechanisms cannot be used, and therefore iteratively outputs the control factors of "low latency priority and strong error correction protection". Iteration process two: For high-definition surveillance video, based on the current high-load scenario and historical bandwidth contention records, the system determines that its bandwidth usage limit must be restricted, and iteratively outputs the control factors of "bandwidth threshold limit and allow frame loss but maintain order".

[0049] S122 outputs several transmission control factors for the data line in this specific scenario: Priority preemption factor: sets industrial control commands to have the highest priority, allowing them to preempt video stream bandwidth; Security policy factor: control commands use "hardware-level fast encryption + forward error correction", and video streams use "selective header encryption"; Link optimization factor: sets the maximum bandwidth share of video streams to 70%, reserving 30% bandwidth as a dedicated channel for control commands. These control factors constitute the core input parameters for the subsequent step S123 to build a "multi-point collaborative control system", ensuring that the data security and transmission quality of critical services are doubly guaranteed in the high-pressure environment of mixed transmission.

[0050] Therefore, a transmission control mechanism for the data line is constructed based on multiple transmission control factors, and multiple data transmission characteristics are extracted. Data security measures for the data line are determined based on the matching of these characteristics and the data type. These security measures encompass privacy protection, error correction, and encryption, taking into account the overall consideration of matching multiple data transmission characteristics and data type. This ensures the accuracy of the data line's data security measures and achieves secure control over the data line. Furthermore, by fully considering the data line's transmission control mechanism and the data type, the accuracy of the data line's data security measures for the data line is improved.

[0051] At this point, based on multiple transmission control factors (such as priority preemption factors and security policy factors), a complete transmission control mechanism is constructed through logical combination and parameterized configuration by the policy engine. This mechanism defines the processing rules for different data streams by the data line, including scheduling priority queues, bandwidth allocation thresholds, and security response levels. It is equivalent to establishing a dynamic set of "traffic regulations" for the data line, ensuring that the subsequent security measures are implemented in a manner that is based on evidence.

[0052] Under the constraints of the control mechanism, the system extracts feature snapshots of the current data stream. This includes not only static features such as packet size and frame structure, but also focuses on dynamic transmission features: timeliness features: data time to life (TTL) and maximum allowable end-to-end delay; robustness features: data tolerance to bit error rate and packet loss retransmission requirements; and streaming pattern features: burst coefficient and packet interval distribution. These features constitute the "demand profile" of data at the transmission layer.

[0053] The system executes a high-precision matching algorithm to associate and map the determined "data type" with the extracted "data transmission characteristics". The matching logic adopts "dual-track verification": it verifies whether the data type conforms to its transmission characteristics (for example, real-time video data usually has the characteristics of high bandwidth and tolerance for packet loss), and it also verifies whether the transmission characteristics meet the constraints of the control mechanism (for example, when the current link is congested, high bandwidth flow may trigger a degradation strategy). Through matching, the system assigns a specific "processing label" to each type of data.

[0054] Based on the matching results, the system dynamically generates a combination of targeted data security measures, which is a multi-dimensional protection system: privacy protection measures: involving data anonymization, masking, or identity authentication, focusing on preventing the leakage of sensitive information; data error correction measures: involving forward error correction coding (FEC), automatic retransmission request (ARQ), or checksum repair, focusing on ensuring data integrity; data encryption measures: involving stream encryption, block encryption, or link layer encryption, focusing on preventing data from being eavesdropped on or tampered with.

[0055] Specifically, the data line is operating under high load, facing the pressure of mixed transmission of industrial control commands and high-definition surveillance video. Based on the output control factors, the system formally constructs the data line's transmission control mechanism. Combining the "priority preemption factor" and the "security strategy factor," this mechanism establishes two sets of parallel processing logic: one is a "hard real-time channel" for low-latency, high-reliability services, and the other is a "flexible transmission channel" for high-bandwidth, latency-tolerant services. This mechanism sets the tone for subsequent processing—control commands take precedence, and video streams adapt.

[0056] The system initiates data transmission feature extraction: For industrial control commands, the system extracts the features of "microsecond-level frame length, periodic bursts, and zero tolerance for packet loss", marking them as having extremely high timeliness requirements; for high-definition surveillance videos, the system extracts the features of "long frame continuity, high throughput, and a certain degree of error tolerance", marking them as having key bandwidth maintenance requirements.

[0057] The system performs feature and type matching: It matches the "industrial control command" type with its "microsecond-level, zero packet loss" characteristics, confirming it belongs to "mission-critical" data and must be processed through the "hard real-time channel." It matches the "high-definition surveillance video" type with its "high throughput, error-tolerant" characteristics, confirming it belongs to "streaming media" data, allocating it to the "flexible transmission channel," and triggering a bandwidth adaptive mechanism. Based on the matching results, the system identifies specific data security measures for the data line: For industrial control commands, security measures focus on "integrity and real-time performance": Privacy protection measures: Key field masking technology is used to obfuscate only the device address and key parameters in the command, reducing processing latency; Data error correction measures: A dual mechanism of strong error correction forward coding (FEC) and immediate automatic retransmission (ARQ) is enabled to ensure that the command bitstream does not flip or get lost under any interference; Data encryption measures: Hardware-level stream encryption algorithms (such as the SNOW3G variant) are used, utilizing hardware accelerators to achieve nanosecond-level encryption, ensuring that commands are not forged in the transmission link.

[0058] For high-definition surveillance video, security measures focus on "bandwidth efficiency and privacy": Privacy protection measures: Implement dynamic desensitization of ROI (Region of Interest), locally blurring faces or sensitive areas in the image, while transmitting the rest of the image to save computing power; Data error correction measures: Use interleaving coding technology to disperse possible continuous burst errors into random errors, utilizing the fault tolerance capability of the video decoder to self-repair and avoid retransmission consuming bandwidth; Data encryption measures: Use lightweight selective encryption, encrypting only the header information of the I-frame (keyframe) of the video frame, while using simple scrambling for P-frames and B-frames, maximizing transmission throughput while ensuring basic security.

[0059] The data cable successfully provides differentiated security protection for the mixed data streams, ensuring both the absolute security and real-time nature of industrial control commands and the smooth transmission of high-definition video streams. This fully demonstrates the adaptability of your proposed dynamic transmission method in complex scenarios.

[0060] Referring to Figure 4, in step S13, the specific steps are as follows: S131: Online monitoring of the data line is performed, and the data transmission path of the data line is presented at the data transmission level. In conjunction with data security measures, multiple key transmission areas of the data line are determined. In each key transmission area, data encryption nodes are determined based on the key transmission area, the data type, and the corresponding transmission environment. Each key transmission area is matched with the corresponding data encryption node to determine multiple data encryption nodes; S132: The location of each data encryption node is marked, and the encryption level is adjusted step by step along the data transmission order of each data encryption node. At the same time, the corresponding data diversion event is determined based on the tracing of the data encryption node. The collaborative management and control framework is determined according to the location of each data encryption node and the corresponding data diversion event. In conjunction with data security measures, a multi-point collaborative management and control system is constructed. At this time, the multi-point collaborative management and control system dynamically coordinates the encryption level and diversion strategy of each data encryption node according to the preset consistency protocol.

[0061] In the embodiments of this application, the data line is monitored online, and the data transmission path of the data line is presented at the data transmission level. In combination with data security measures, multiple key transmission areas of the data line are determined. In each key transmission area, a data encryption node is determined based on the key transmission area, the data type, and the corresponding transmission environment. Each key transmission area is matched with a corresponding data encryption node to determine multiple data encryption nodes. This approach takes into account the overall consideration of key transmission areas, data type, and corresponding transmission environment, ensuring the accuracy of the data encryption nodes.

[0062] At this point, by deploying online monitoring probes, the flow of data inside the data line is captured in real time. The system no longer regards the data line as a simple "pipe" but interprets it as a miniature transmission topology network. Through signal reflection testing and timing analysis, the system presents the complete transmission path of data from interface input, through internal signal conditioning, and then to interface output at the logical level, clarifying the timing position of the data flow in each physical segment.

[0063] Based on the presented transmission path and combined with the data security measures determined in S123, the system identifies and divides several "critical transmission areas." The division is based on abrupt changes in security requirements: High-sensitivity areas: segments where the data payload is completely exposed and easily eavesdropped by physical probes; High-interference areas: segments where signal attenuation is severe or the electromagnetic environment is complex, requiring error correction and integrity protection; Buffer scheduling areas: segments where data flows converge, are scheduled and buffered, facing the risk of buffer overflow attacks. These areas are not fixed but are dynamically defined according to the type of data flow and security requirements.

[0064] Within each critical transmission area, the system executes refined node location logic. Input variables include: critical transmission area attributes: whether the area prioritizes anti-eavesdropping or anti-interference; data type: whether the data is real-time control stream or ordinary video stream; transmission environment: current signal-to-noise ratio and computing resources; and indicating where in the path to insert encryption / decryption or processing nodes to maximize efficiency (e.g., performing error correction coding before signal attenuation, or completing encryption before entering a high-interference area). The system locks down specific "data encryption nodes" within each critical transmission area. These "nodes" can be logic processing units in physical circuits or specific field positions in data frame structures. The system establishes a one-to-one mapping relationship between areas and nodes, forming a distributed security protection network covering the entire path.

[0065] Specifically, the system initiates online monitoring of the data line; the monitoring probe provides real-time feedback on the transmission delay and signal level of the data stream on the twisted pair inside the data line, constructing a clear transmission path: from the "industrial gateway interface end" through the "signal enhancement section in the middle of the cable" and finally reaching the "core switching backplane end".

[0066] Based on this path, and combined with the differentiated security measures for the two types of data in S123, the system divides into three key transmission areas: Area 1 (interface access area): located at the data line entrance, it is the convergence point of mixed data streams, and faces the main risks of unauthorized access and data sniffing; Area 2 (long-distance transmission area): located in the middle of the cable, crossing a complex industrial electromagnetic environment, and faces the main risks of signal attenuation and bit flipping caused by interference; Area 3 (backplane output area): located at the end of the data line, it faces the risk of high-bandwidth data overflow.

[0067] The system determines data encryption nodes in each area based on multi-factor logic: For industrial control commands: In Area 1 (interface access area), considering its "high privacy" security measures, the system determines a source encryption node. This node is responsible for hardware-level stream encryption of the command payload before the data enters the main cable channel to prevent physical-level signal interception; In Area 2 (long-distance transmission area), combining "strong error correction" security measures with a "high interference" transmission environment, the system determines an intermediate error correction enhancement node. This node does not perform traditional encryption, but embeds forward error correction coding logic as part of data security to ensure that control commands remain intact under strong interference.

[0068] For high-definition surveillance video: In Zone 1 (interface access area), based on the "lightweight encryption" method, the system matches a header obfuscation node to only scramble the video frame header, reducing processing overhead; In Zone 3 (backplane output area), considering the high bandwidth characteristics of the video stream and the "overflow prevention" requirement, the system determines a traffic shaping node to smooth the video data and perform cache verification to prevent it from impacting the backend equipment.

[0069] The data line identifies multiple data encryption nodes along the transmission path, including "source encryption node", "intermediate error correction enhancement node", "header obfuscation node" and "traffic shaping node". These nodes are precisely matched with key transmission areas, constructing a multi-point collaborative security skeleton for mixed transmission tasks, providing specific physical / logical support for building a "multi-point collaborative management and control system" in the subsequent step S132.

[0070] Furthermore, the location of each data encryption node is marked, and the encryption level is adjusted step by step along the data transmission sequence of each data encryption node. At the same time, the corresponding data diversion event is determined based on the tracing of the data encryption node. A collaborative management and control framework is determined based on the location of each data encryption node and the corresponding data diversion event. A multi-point collaborative management and control system is constructed in conjunction with data security measures. At this time, the multi-point collaborative management and control system dynamically coordinates the encryption level and diversion strategy of each data encryption node according to the preset consistency protocol, which is compatible with the overall consideration of tracing the data encryption node and ensures the accuracy of the corresponding data diversion event.

[0071] At this point, the system performs logical addressing and location marking on each data encryption node determined in S131, forming an ordered node sequence. Subsequently, along the transmission direction of the data flow, the system executes a "step-by-step control" strategy. This is not a simple linear increase or decrease, but rather a dynamic adjustment of the encryption strength based on the depth of data flow and the risk exposure surface. For example, high-strength encryption is used at the data entry point to prevent eavesdropping, lightweight encryption is used in the internal transmission segment to reduce latency, or the encryption level is increased before the data splitting point to ensure the secure isolation of branch data.

[0072] The system performs historical and real-time behavior tracking analysis on each data encryption node; it focuses on identifying whether a node exhibits "data splitting" behavior, i.e., whether the data stream is copied, forwarded, or split into multiple sub-streams at that node; splitting events often signify a topological change in the data transmission path and are also key points for the spread of security risks. Through tracing, the system clarifies which nodes are purely transmission nodes and which are branch nodes with distribution capabilities.

[0073] Based on the location information of nodes and the characteristics of diversion events, the system constructs a collaborative management and control framework. This framework defines the hierarchical relationship between nodes (such as parent-child nodes, master-slave nodes) and the data flow topology. If a node has a diversion event, the node is defined as a "key collaborative point" in the framework. The system will configure additional monitoring resources for it and establish its linkage logic with downstream branch nodes.

[0074] Based on the data security measures defined in S123, the system formally generates a multi-point collaborative management and control system. This system introduces a "preset consistency protocol" (such as a simplified industrial version of a Paxos or Raft mechanism) to ensure that all nodes maintain consistency when adjusting strategies. The system dynamically coordinates the encryption level and traffic splitting strategy of each node: when the encryption level of an upstream node is increased, the downstream node synchronously increases its decryption and verification computing power; when traffic splitting occurs, the traffic splitting strategy automatically transmits the security context to all branches to ensure that the data remains under control after the splitting.

[0075] Specifically, the system marks the locations of the identified nodes, forming a transmission sequence of "source encryption node (location A) — intermediate error correction enhancement node (location B) — traffic shaping node (location C)". The system then initiates a step-by-step adjustment of the encryption level: for industrial control commands, the highest level of stream encryption (Level-3) is set at location A (source). At location B, due to the need for error correction coding, the system adjusts the encryption level to an intermediate state (Level-2, protecting only the header) to ensure that the error correction logic can intervene normally. For high-definition surveillance video, lightweight obfuscation (Level-1) is used at location A. The system maintains this level until location C (traffic shaping) to avoid wasting computing power caused by repeated encryption and decryption.

[0076] The system traces data diversion events; monitoring reveals a critical diversion in the middle to later stages of the data transmission path: some high-definition surveillance video streams need to be diverted to the local storage module at the edge, while industrial control commands go directly to the core control unit; based on this, the system confirms location C as a "diversion node" with a clear diversion event; based on this, the system constructs a collaborative management and control framework; in this framework, the traffic shaping node at location C is marked as the "master node," and its two downstream branches (the local storage branch and the core control branch) are marked as "slave nodes"; the framework clarifies the security responsibility transfer relationship after data diversion.

[0077] Combined with corresponding security measures, the system generates a multi-point collaborative management and control system and dynamically coordinates based on a consistency protocol: when the source of the data line (location A) detects an external attack threat and upgrades the encryption level to Level-4, the consistency protocol is triggered instantly, notifying the error correction node at location B to synchronously update the decryption key and verification logic, preventing the error correction module from being unable to recognize the frame structure due to the encryption upgrade; for the diversion event at location C, the system dynamically adjusts the diversion strategy: the system automatically passes the "lightweight encryption context" of the video stream to the local storage branch, ensuring that the diverted video data remains encrypted when written to storage, without needing to be re-encrypted; at the same time, the system coordinates with location C to open a dedicated channel (high-priority diversion strategy) for industrial control commands at the moment of diversion, ensuring that they are not squeezed by the bandwidth of the video diversion operation; the data line successfully constructs a multi-point collaborative management and control system with dynamically adjustable encryption levels and real-time linkage of diversion strategies, ensuring that both types of data can safely and efficiently reach their destination in mixed transmission and complex diversion scenarios.

[0078] Referring to Figure 5, the specific steps in step S14 are as follows: S141: Dynamically monitor the multi-point collaborative management and control system, and activate the edge computing mechanism of each data encryption node based on the multi-point collaborative management and control system. Each data encryption node marks the data segments it passes through, so as to compare the deviation between the data received sequence and the expected sequence of each data encryption node in real time, and construct a heat map of the data transmission progress on the data line. Based on the heat map of the transmission progress, the data transmission progress and the feedback delay information of each data encryption node are presented; S142: Collect the data transmission progress in real time, and perform multi-dimensional coupling analysis on the data transmission progress, data type, and preset data transmission requirements. As the analysis progresses, multiple data transmission elements are determined. Based on the matching of multiple data transmission elements and the preset data transmission mode matching table, the data transmission mode of the data line is determined. The data transmission modes include full transmission mode, key frame priority transmission mode, and partial frame synchronous transmission mode; S143: The data transmission mode will dynamically switch according to the comparison results between the transmission progress and the preset progress requirements, and optimize the dynamic transmission process of the data line. At this time, the optimization command is sent to the data line in real time to dynamically adjust the signal modulation and demodulation strategy and power management status of the data line.

[0079] In the embodiments of this application, a dynamic monitoring multi-point collaborative management and control system is established, and the edge computing mechanism of each data encryption node is activated based on the multi-point collaborative management and control system. Each data encryption node marks the data segments that pass through, so as to compare the deviation between the data receiving sequence and the expected sequence of each data encryption node in real time, and construct a heat map of the data transmission progress on the data line. The heat map of the transmission progress presents the data transmission progress and the feedback delay information of each data encryption node. The heat map of the transmission progress presents the data transmission progress and the feedback delay information of each data encryption node.

[0080] At this point, the system implements full-link dynamic monitoring of the control system built by S132 to maintain the connection of the heartbeat signal. Subsequently, it issues instructions to each data encryption node to activate its built-in edge computing mechanism. This means that the node is no longer just a passive data transmission channel or encryption executor, but has local computing power scheduling capabilities. It can independently complete the feature extraction, comparison and anomaly judgment of data segments without having to send all the original data back to the main control terminal for processing, thereby greatly reducing monitoring latency.

[0081] Driven by edge computing mechanisms, each node performs fine-grained segment marking on the data flowing through it (such as sliding window slicing based on timestamps or sequence numbers); received sequence: nodes record the actual order of received data segments in real time; expected sequence: based on the communication protocol and the agreement of the sender, nodes maintain an ideal sequence that should theoretically be received; the system compares the two in real time and calculates the sequence deviation value; the deviation value reflects the orderliness and integrity of data transmission, and a surge in the deviation value indicates the occurrence of out-of-order, packet loss or link congestion.

[0082] The system collects real-time status data from each node and constructs a transmission progress heatmap using an interpolation algorithm. This heatmap is not a geographical map, but a logical topology map: Dimension X: the transmission order of data encryption nodes (from source to destination); Dimension Y: time axis; Heat value (color depth): represents the data transmission progress (the percentage of data already transmitted); The heatmap can intuitively show the speed of data flow in each segment of the data line and identify "cold spots" (transmission stagnation areas) and "hot spots" (high-speed transmission areas).

[0083] The system performs in-depth analysis based on heatmaps and outputs two key layers of information: transmission progress: combining the amount of data received by each node to accurately calculate the percentage of the data stream's position in the entire link; feedback latency information: calculating the time difference between each node's response to the central control command or feedback status; high latency often means that the node's computing power is overloaded or the physical delay of the link is too large, which is a potential system bottleneck indicator.

[0084] Specifically, the system initiates monitoring of the multi-point collaborative management and control system and issues activation instructions to the "source encryption node", "intermediate error correction node" and "traffic shaping node" deployed within the data line to activate the edge computing mechanism. This enables each node to independently process data flow characteristics. For example, the "intermediate error correction node" can independently determine whether error correction coding is needed without waiting for instructions from the master control end.

[0085] Each node begins segmenting the mixed data stream: for industrial control commands, the node marks them as "high-priority sequence blocks" and strictly monitors their sequence numbers; the system compares them in real time and finds that the received sequence of the control commands is completely consistent with the expected sequence, with a deviation value of 0, proving that its transmission within the dedicated channel is extremely orderly; for high-definition surveillance video, the node marks it as "streaming media sequence blocks"; due to the video stream using a complex compression algorithm and buffering scheduling when passing through the "traffic shaping node", the system detects a slight out-of-order (deviation value fluctuation) in the received sequence of this node, but it is still within the fault tolerance range allowed by the protocol.

[0086] Based on the above data, the system constructs a real-time transmission progress heatmap: at the beginning of the heatmap (corresponding to the source encryption node), the heat value is dark red, indicating an extremely high data injection rate; in the middle of the heatmap (corresponding to the intermediate error correction node), the heat value remains stable, indicating smooth transmission; at the end of the heatmap (corresponding to the traffic shaping node), brief orange stripes appear for the video stream portion, indicating that the data propagation speed in this area has slightly decreased due to traffic splitting and shaping operations.

[0087] The system clearly presents the transmission progress and feedback delay based on the heat map: The transmission progress shows that the industrial control command has been transmitted to the end of the link, with a progress of 95%, while the overall progress of the high-definition monitoring video is 60% due to the large amount of data; The feedback delay information shows that the feedback delay of the traffic shaping node has slightly increased to 5 milliseconds (normally it is 1 millisecond). Based on this, the system judges that the node is currently under high intensity of traffic splitting calculation pressure. This key information is then used as an input parameter and passed to the subsequent step S142 to decide whether it is necessary to dynamically adjust the transmission mode or bandwidth allocation of the node to prevent the video splitting operation from interfering with the real-time performance of the control command.

[0088] Furthermore, the data transmission progress is collected in real time, and the data transmission progress is coupled with the data type and preset data transmission requirements for multi-dimensional analysis. As the analysis progresses, multiple data transmission elements are determined. Based on the matching of multiple data transmission elements and the preset data transmission mode matching table, the data transmission mode of the data line is determined. The data transmission modes include full transmission mode, key frame priority transmission mode, and local frame synchronous transmission mode. This comprehensive consideration of matching multiple data transmission elements and the preset data transmission mode matching table ensures the accuracy of the data transmission mode of the data line.

[0089] At this time, the system collects the transmission progress data output by S141 at a millisecond frequency and uses it as a core variable to perform multi-dimensional coupling analysis with "data type" and "preset data transmission requirements" (such as maximum allowable delay, minimum throughput, and packet loss rate threshold); coupling logic: the system evaluates whether the current transmission progress meets the transmission requirements of the data type in a specific scenario; for example, if the progress lags behind the preset time window, the "urgency factor" is triggered; if the progress is ahead of schedule and the bandwidth is sufficient, the "robustness factor" is triggered.

[0090] As the coupling analysis deepens, the system identifies the key variables that determine the transmission strategy, namely the "data transmission elements." These elements are a high-level summary of the current transmission contradictions and mainly include: timeliness deviation: the difference between the current transmission delay and the service tolerance limit; link load rate: the ratio of the current bandwidth occupancy to the total link capacity; and data sensitivity weight: the criticality of data (such as the difference between I-frames and P-frames, and the difference between control commands and heartbeat signals). These elements constitute the input vector for matching the transmission mode.

[0091] The system has a built-in "data transmission mode matching table," which is a decision matrix based on historical experience and algorithm simulation. The rows and columns of the matrix correspond to different combinations of transmission elements. The system inputs the extracted "data transmission element" vector into this matrix and uses feature matching algorithms (such as nearest neighbor search or rule tree traversal) to lock in the most matching transmission mode. At the same time, the system finally determines the working mode of the data line, mainly covering three forms: full transmission mode: suitable for scenarios with excellent link status, extremely high integrity requirements, and no bandwidth bottlenecks, ensuring that every bit is transmitted without loss; key frame priority transmission mode: suitable for bandwidth-constrained or high real-time scenarios, where the system identifies key frames in the data (such as control commands, video I-frames) and sends them first, while secondary data is temporarily buffered or downgraded; partial frame synchronous transmission mode: suitable for scenarios with severe congestion or extremely low latency requirements, transmitting only the minimum subset of data required to maintain system synchronization, or selectively discarding data to maintain core functions.

[0092] Specifically, the system collects the transmission progress in real time. According to the feedback from S141, the transmission progress of industrial control commands is currently fast and is close to the end of the link, while the transmission progress of high-definition monitoring video is only 60% complete due to diversion operation and bandwidth limitations, and a slight backlog has occurred.

[0093] The system performs multi-dimensional coupling analysis: For industrial control commands, the system couples their progress with "microsecond-level latency requirements"; the analysis shows that although the progress is relatively fast, due to the high load of the overall link, its timeliness deviation is decreasing (i.e., the safety margin is decreasing), and it must be ensured that it is not blocked by subsequent video streams; For high-definition surveillance video, the system couples its progress with "smoothness requirements"; the analysis shows that the current transmission progress lags behind the standard frame rate playback rate, and if full transmission continues, it may cause stuttering at the receiving end.

[0094] Based on the above analysis, the system extracts the key data transmission elements: Element 1: The "extremely low latency requirement" of the control command and the "high bandwidth usage" of the video stream create resource competition; Element 2: The link load rate has reached 85%, which is close to saturation; Element 3: The I-frames (key frames) in the video data have been transmitted, and the subsequent ones are mainly P-frames and B-frames (predicted frames).

[0095] The system inputs these elements into a data transmission mode matching table: For control commands, the matching table determines that they meet the "high priority, small packet characteristics," but due to the high overall link load, the system decides to maintain their original high priority channel without adding any extra redundancy, confirming it as a "key frame priority transmission mode" (here, control commands are regarded as the core of the "key frame" in the data stream); For high-definition surveillance video, the matching table determines that the current "high load, delayed progress" and the subsequent frames are predicted frames. If full transmission is forced, it will cause overall link congestion, thereby dragging down control commands; therefore, the system matches it with a "partial frame synchronous transmission mode."

[0096] The data line determines and switches to a hybrid operating state: It implements a key frame priority transmission mode for industrial control commands, ensuring absolute priority in congested links and guaranteeing the real-time performance of the control loop; it implements a partial frame synchronous transmission mode for high-definition surveillance video, intelligently discarding some non-critical video prediction frames (B-frames) and retaining only key frames and some P-frames to maintain basic video continuity, significantly reducing bandwidth usage and releasing link resources. Through the execution of S142, the data line successfully balances the contradiction between "control real-time performance" and "monitoring visibility" under the high-pressure environment of hybrid transmission, avoiding the risk of control command paralysis due to excessive video stream transmission. This process fully verifies the adaptive advantages of your proposed method in complex dynamic scenarios.

[0097] Therefore, the data transmission mode will dynamically switch according to the comparison between the transmission progress and the preset progress requirements, and optimize the dynamic transmission process of the data line. At this time, the optimization command will be sent to the data line in real time to dynamically adjust the signal modulation and demodulation strategy and power management status of the data line. The dynamic adjustment of the signal modulation and demodulation strategy and power management status of the data line is introduced. At the same time, a multi-point collaborative control system is introduced to perform encryption control on multiple data encryption nodes of the data line and to deeply control the data transmission mode of the data line in order to optimize the dynamic transmission process of the data line, and to achieve both online security control and transmission efficiency.

[0098] At this point, a sliding monitoring window is introduced to continuously calculate the deviation vector between the "actual transmission progress" and the "preset progress requirement". The preset requirement includes not only time nodes but also data integrity indicators. The system triggers the threshold judgment logic for mode switching based on the deviation direction (positive deviation indicates progress ahead and negative deviation indicates progress behind) and deviation magnitude to ensure that the switching decision is real-time and data-supported.

[0099] Based on the deviation comparison results, the system executes the state machine's transition logic. If a continuous positive deviation (resource surplus) is detected, the system may switch from aggressive mode to energy-saving mode. If a negative deviation (resource scarcity) is detected, the system switches in the opposite direction. Process optimization focuses on replanning the data transmission queue, adjusting the data packet transmission interval and packet size to adapt to the upcoming changes in the physical link state. At the same time, the system generates an optimized instruction frame containing control words, which is sent to the data line's interface controller in real time with the highest priority through the in-band control channel or out-of-band management channel. The instruction content encapsulates the modulation parameter set (such as symbol rate and modulation order) and power parameter set (such as voltage amplitude and sleep timing) to ensure that the physical layer can respond to the scheduling requirements of the logic layer in a timely manner.

[0100] The system dynamically modulates the modulation and demodulation scheme through programmable logic circuits: High-order modulation strategy: When the signal-to-noise ratio is good, high-order modulation (such as 16-PAM or QAM) is used to improve the bit throughput per unit time; Robust modulation strategy: When the interference is severe or the signal attenuation is large, it falls back to low-order modulation (such as 2-PAM or BPSK). Although the rate is sacrificed, the anti-interference ability and transmission reliability are greatly improved.

[0101] The system dynamically adjusts the power management unit (PMU) of the data line interface chip; for high-load transmission tasks, it increases the supply voltage to enhance the driving capability and ensures a steep signal rise edge; for idle or low-priority transmission stages, it reduces the clock frequency or enters a low-power sleep state to reduce thermal noise interference and extend the device life.

[0102] Specifically, the system dynamically compares the transmission progress with the preset requirements. Monitoring revealed that due to sudden strong electromagnetic interference at the industrial site, the local frame synchronous transmission mode of the high-definition monitoring video caused its actual transmission progress to lag behind the preset requirements by about 15%, resulting in a negative deviation. However, the industrial control commands, being in the key frame priority transmission mode, although delayed, were still within an acceptable timeout window. The system determined that the physical carrying capacity of the current link was insufficient to support the predetermined transmission rate and physical layer optimization was necessary.

[0103] The system triggers dynamic switching and process optimization of data transmission mode; for video streams, the system decides to temporarily freeze the transmission of some non-critical data, optimize the transmission process, and concentrate limited link resources to ensure the passage of control commands; at the same time, it prepares to adjust physical layer parameters to combat interference; the system generates optimization commands and issues them in real time; the command frame arrives instantly at the interface controller of the data line, instructing it to enter the "strong anti-interference transmission state".

[0104] The system dynamically adjusts the signal modulation and demodulation strategy: In response to the current high bit error rate risk of the data line, the system dynamically reverts the modulation strategy from the high-throughput 16-PAM (sixteen-pulse amplitude modulation) to 2-PAM (binary pulse amplitude modulation, i.e. NRZ coding). Although this adjustment halves the theoretical bandwidth, it greatly enhances the opening of the signal eye diagram, ensuring that even in a strong noise background, weak control command signals can still be accurately judged by the receiver, avoiding retransmission storms caused by bit errors.

[0105] The system synchronously performs adaptive configuration of power management status: In order to counteract signal attenuation caused by interference, the system increases the data line interface drive voltage by 10% through PMU, enhances the slew rate of differential signal, and significantly enhances the signal's anti-common-mode interference capability on the transmission line; For idle time slots where control command transmission has been completed, the system immediately starts intermittent sleep mode to reduce chip heat generation and reduce thermal noise interference to subsequent weak signal detection.

[0106] Through the closed-loop execution of S143, the data line successfully resisted sudden electromagnetic interference. Although the video stream bandwidth was further reduced due to the modulation strategy rollback, the critical industrial control command link was able to remain uninterrupted, achieving dynamic survival and transmission. This perfectly illustrates the engineering value of the data line dynamic transmission method based on data security that you proposed.

[0107] Please refer to Figure 6, which is a schematic diagram of the structural composition of the dynamic transmission system based on data security data lines in an embodiment of the present invention. The dynamic transmission system based on data security data lines is applied to the aforementioned dynamic transmission method based on data security data lines. The dynamic transmission system based on data security data lines includes: a data type module 21, used for data transmission via the data line, and configured with a corresponding data security module during data transmission. At this time, the data security module identifies the data, and determines the corresponding data type based on the identification result and the data signal output by the data line; a data security module 22, used to determine the scenario where the data line is located based on the tracing of the data line, and according to the scenario and the data security module... The data security mechanism and past transmission events of the data line determine the transmission control mechanism of the data line, and determine the data security measures for the data line based on the data type. The multi-point collaborative control system module 23 is used to mark the transmission path of the data line and mark multiple data encryption nodes in the data line. The multi-point collaborative control system is determined based on the location of each data encryption node, the corresponding data diversion event, and the data security measures. The dynamic transmission module 24 is used to determine the transmission progress of the data based on the dynamic identification of the multi-point collaborative control system, and determine the data transmission mode of the data line based on the data type and corresponding data transmission requirements, and optimize the dynamic transmission process of the data line.

[0108] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A dynamic transmission method based on a data security data cable, characterized in that, include: The data cable transmits data and is equipped with a corresponding data security module during data transmission. This module identifies the data and determines the data type based on the identification result and the data signal output by the data cable. The scenario in which the data cable is located is determined by tracing its origins. Based on this scenario, the data security mechanism of the data security module, and past transmission events of the data cable, the transmission control mechanism of the data cable is determined. The data security measures for the data cable are also determined by considering the data type. The data transmission path on the data cable is marked, and multiple data encryption nodes are marked within the data cable. A multi-point collaborative control system is determined based on the location of each data encryption node, the corresponding data diversion events, and the data security measures. In this multi-point collaborative control system, the data transmission progress is determined based on the dynamic identification of the multi-point collaborative control system, and the data transmission mode of the data line is determined in combination with the data type and corresponding data transmission requirements, and the dynamic transmission process of the data line is optimized.

2. The dynamic transmission method based on a data security data line according to claim 1, characterized in that, The data line transmits data and is equipped with a corresponding data security module during data transmission. At this time, the data security module identifies the data and determines the corresponding data type based on the identification result and the data signal output by the data line. This includes: real-time monitoring of the data transmission of the data line, the data line being equipped with a corresponding data security module, the data passing through the data security module during transmission, triggering the data security module to dynamically identify the data, and performing multi-dimensional scanning of the data payload, protocol characteristics, and content to match the corresponding identification result for the data.

3. The dynamic transmission method based on a data security data line according to claim 2, characterized in that, The data line transmits data and is equipped with a corresponding data security module during data transmission. At this time, the data security module identifies the data and determines the corresponding data type based on the identification result and the data signal output by the data line. The method also includes: acquiring the data signal output by the data line, determining the data attribute by parsing the data signal, performing multi-level iterations on the data attribute and identification result, and gradually determining the data type of the data during the iteration process, so as to determine the data type of the data in multiple dimensions.

4. The dynamic transmission method based on a data security data line according to claim 1, characterized in that, The process of determining the scenario of the data line based on its tracing involves determining the transmission control mechanism of the data line based on the scenario, the data security mechanism of the data security module, and the data line's past transmission events, and determining the data security measures for the data line in conjunction with the data type. This includes: tracing the data line and determining the port routing route of the data line during the tracing process; determining the primary scenario of the data line along the port routing route, the corresponding hardware configuration, and the corresponding transmission environment; and combining the timestamp sequence of the data line with the data throughput to perform multi-factor fusion to determine the scenario of the data line.

5. The dynamic transmission method based on a data security data line according to claim 4, characterized in that, The process of determining the scenario where the data line is located based on its tracing, determining the transmission control mechanism of the data line based on the scenario, the data security mechanism of the data security module, and the data line's past transmission events, and determining the data security measures for the data line in conjunction with the data type, further includes: marking the data security module, determining the corresponding data security library based on the data security module's self-identification, determining the corresponding data security mechanism based on the traversal of the data security library, collecting past transmission events of the data line, performing multi-factor iteration on the scenario, the data security mechanism of the data security module, and the past transmission events of the data line, and outputting multiple transmission control factors of the data line in the scenario; constructing the transmission control mechanism of the data line based on the multiple transmission control factors, extracting multiple data transmission features, and determining the data security measures for the data line in relation to the data based on the matching of multiple data transmission features and the data type, which include privacy protection measures, data error correction measures, and data encryption measures.

6. The dynamic transmission method based on a data security data line according to claim 1, characterized in that, The data is marked along the transmission path of the data line, and multiple data encryption nodes are marked in the data line. A multi-point collaborative management and control system is determined based on the location of each data encryption node, the corresponding data diversion event, and data security measures. This includes: online monitoring of the data line, presenting the data transmission path of the data line at the data transmission level, and determining multiple key transmission areas of the data line in conjunction with data security measures. In each key transmission area, data encryption nodes are determined based on the key transmission area, the data type, and the corresponding transmission environment. Each key transmission area is matched with a corresponding data encryption node to determine multiple data encryption nodes.

7. The dynamic transmission method based on a data security data line according to claim 6, characterized in that, The process involves marking the transmission path of the data on the data line and marking multiple data encryption nodes within the data line. A multi-point collaborative management system is determined based on the location of each data encryption node, the corresponding data diversion event, and data security measures. This also includes marking the location of each data encryption node and progressively adjusting the encryption level along the data transmission sequence of each node. Simultaneously, the corresponding data diversion event is determined based on the tracing of the data encryption node. A collaborative management framework is determined based on the location of each data encryption node and the corresponding data diversion event. A multi-point collaborative management system is then constructed in conjunction with data security measures. At this point, the multi-point collaborative management system dynamically coordinates the encryption level and diversion strategy of each data encryption node according to a preset consistency protocol.

8. The dynamic transmission method based on a data security data line according to claim 1, characterized in that, In this multi-point collaborative control system, the data transmission progress is determined based on the dynamic identification of the multi-point collaborative control system, and the data transmission mode of the data line is determined in combination with the data type and corresponding data transmission requirements. The dynamic transmission process of the data line is optimized, including: dynamically monitoring the multi-point collaborative control system, activating the edge computing mechanism of each data encryption node based on the multi-point collaborative control system, marking the data segments passed by each data encryption node to compare the deviation between the data received sequence and the expected sequence of each data encryption node in real time, and constructing a heat map of the data transmission progress on the data line. The heat map of the transmission progress presents the data transmission progress and the feedback delay information of each data encryption node.

9. The dynamic transmission method based on a data security data line according to claim 8, characterized in that, In this multi-point collaborative control system, the data transmission progress is determined based on the dynamic identification of the multi-point collaborative control system. The data transmission mode of the data line is determined by combining the data type and corresponding data transmission requirements, and the dynamic transmission process of the data line is optimized. This also includes: real-time acquisition of the data transmission progress, and multi-dimensional coupling analysis of the data transmission progress with the data type and preset data transmission requirements. As the analysis progresses, multiple data transmission elements are determined. The data transmission mode of the data line is determined based on the matching of multiple data transmission elements with a preset data transmission mode matching table. The data transmission modes include full transmission mode, key frame priority transmission mode, and partial frame synchronous transmission mode. The data transmission mode dynamically switches based on the comparison between the transmission progress and the preset progress requirements, optimizing the dynamic transmission process of the data line. At this time, optimization instructions are sent to the data line in real time to dynamically adjust the signal modulation and demodulation strategy and power management status of the data line.

10. A dynamic transmission system based on a data security data cable, characterized in that, The dynamic transmission system based on data security data lines is applied to the dynamic transmission method based on data security data lines as described in any one of claims 1-9; The dynamic transmission system based on data security data lines includes: a data type module for transmitting data via the data line, configured with a corresponding data security module during data transmission. This data security module identifies the data and determines the corresponding data type based on the identification result and the data signal output by the data line; a data security module for determining the scenario of the data line based on its traceability, determining the transmission control mechanism of the data line based on the scenario, the data security mechanism of the data security module, and past transmission events of the data line, and determining the data security measures for the data line based on the data type; a multi-point collaborative control system module for marking the data transmission path on the data line and marking multiple data encryption nodes within the data line, determining the multi-point collaborative control system based on the location of each data encryption node, the corresponding data diversion events, and the data security measures; and a dynamic transmission module for determining the data transmission progress based on the dynamic identification of the multi-point collaborative control system, determining the data transmission mode of the data line based on the data type and corresponding data transmission requirements, and optimizing the dynamic transmission process of the data line.

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