Circulation data supervision method based on data interaction

Abstract

The invention discloses a circulation data supervision method based on data interaction, and belongs to the technical field of data supervision, and the method specifically comprises the steps: building a dynamic identification system in a data circulation process, and generating a unique dynamic identifier when each data unit initiates interaction, the dynamic identifier is subjected to irreversible chained updating along with each data interaction behavior; setting an environment sensing node in a circulation path, collecting a network topology state, equipment physical position offset and transmission medium electromagnetic characteristic parameters in real time when data interaction occurs, and generating an environment fingerprint data packet; carrying out asynchronous binding on the dynamic identifier and the environment fingerprint data packet to form a supervision index with space-time relevance; when cross-domain circulation occurs in the data unit, reconstructing a three-dimensional track model of a data circulation path by reversely analyzing the environment fingerprint data packet in the supervision index; according to the invention, the efficiency and accuracy of data circulation supervision are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data supervision, and particularly relates to a method for supervising circulation data based on data interaction. Background Art

[0002] With the rapid development of the digital economy, data has become a key production factor, and the frequent circulation and interaction of data among multiple entities and multiple systems have become the norm.

[0003] Currently, data circulation supervision mainly adopts a combination of static identification and post-event auditing. Static identification usually assigns a fixed label when data is generated, which is difficult to adapt to the characteristic changes of data during the dynamic interaction process; post-event auditing relies on manual or simple log analysis, which requires a large amount of human and time costs, and there is a lag in supervision. In addition, although some supervision methods introduce the concept of dynamic identification, when data crosses domains, it is difficult to accurately track the actual circulation path of the data, and there is a lack of effective perception and recording of the network environment and physical environment where the data is located.

[0004] There are many deficiencies in the existing data circulation supervision technologies. The static identification method cannot accurately reflect the transfer state of data in real time when facing complex and changeable data interaction scenarios; and there is a lack of effective perception of the data interaction environment, making it difficult to construct a complete and accurate circulation trajectory when data crosses domains, and unable to meet the strict requirements of current data security supervision for traceability and verifiability of the entire data life cycle. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for supervising circulation data based on data interaction, and solve the following technical problems: The static identification method cannot accurately reflect the transfer state of data in real time when facing complex and changeable data interaction scenarios; and there is a lack of effective perception of the data interaction environment, making it difficult to construct a complete and accurate circulation trajectory when data crosses domains.

[0006] The purpose of the present invention can be achieved by the following technical solutions: A method for supervising circulation data based on data interaction, comprising the following steps: Establish a dynamic identification system during the data flow process. Each data unit generates a unique dynamic identifier when initiating an interaction. The identifier is synthesized by the data content characteristic value, the interaction timestamp, and the target recipient identity code through a one-way conversion algorithm. The dynamic identifier undergoes an irreversible chain update with each data interaction behavior; An environmental perception node is set in the circulation path to collect the network topology state, the physical position offset of the device, and the electromagnetic characteristic parameters of the transmission medium in real time when data interaction occurs, and generate an environmental fingerprint data packet; asynchronously bind the dynamic identifier to the environmental fingerprint data packet to form a regulatory index with spatio-temporal correlation; When the data unit undergoes cross-domain circulation, the three-dimensional trajectory model of the data circulation path is reconstructed by reverse-analyzing the environmental fingerprint data packet in the regulatory index.

[0007] As a further solution of the present invention: the generation process of the dynamic identifier specifically includes: When the data unit is ready to be sent, extract the check value of the bytes at fixed intervals in its binary sequence as the content feature value, use the difference between the local clock of the sender and the standard time source as the timestamp correction factor, and use the truncated hash value of the unique identification code of its hardware device as the receiver identity code; input the three into the elliptic curve function for non-linear mapping to generate the initial dynamic identifier; in each subsequent forwarding, perform an exclusive OR operation on the last byte of the previous identifier and the identity code of the new receiver, and insert the operation result into the head of the identifier to form an updated dynamic identifier chain.

[0008] As a further solution of the present invention: the generation of the environmental fingerprint data packet includes the following steps: Deploy multi-axis motion sensors at the physical device where data interaction occurs to continuously monitor the three-dimensional acceleration and angular velocity changes of the device. When a data transmission instruction is detected, record the motion trajectory waveform within a set time window before and after the interaction; at the same time, collect the signal strength matrix of the wireless access point where the device is located, and extract the phase offset of each channel carrier frequency; after time-domain alignment of the motion trajectory waveform and the phase offset, use wavelet transform to extract the energy distribution map of the characteristic frequency band, quantize it into a multi-dimensional vector and attach the geographical fence coordinates of the device to form the basic data layer of the environmental fingerprint.

[0009] As a further solution of the present invention: the asynchronous binding process is specifically as follows: after the data unit completes the interactive transmission, split the dynamic identifier into a head verification segment and a tail check segment. The head verification segment performs spatial coding conversion with the device geographical coordinates in the environmental fingerprint data packet to generate a positioning hash value; the tail check segment performs a convolution operation with the waveform features collected by the motion sensor to generate a physical feature mark; splice the positioning hash value and the physical feature mark in the order of transmission time to form a verification chain of the regulatory index, and this verification chain is split and stored in the storage nodes in different geographical regions of the interactive path in a distributed storage manner.

[0010] As a further solution of the present invention: The reconstruction method of the three-dimensional trajectory model includes: extracting the positioning hash values corresponding to each interaction from the supervision index, and restoring the geographical coordinate sequence of the device through inverse space encoding; at the same time, parsing the waveform parameters in the physical feature markers, and calculating the motion correlation coefficient between adjacent nodes; combining the network topology state data, establishing a propagation path surface model based on the geographical coordinate system, superimposing the device motion vector field on the surface model, and generating a three-dimensional circulation trajectory through the streamline tracking algorithm of fluid mechanics. This trajectory model can be dynamically scaled and displayed along the time axis.

[0011] As a further solution of the present invention: The distributed storage of the verification chain adopts a sharding redundancy strategy. Each supervision index is split into three parts: geographical positioning shard, device feature shard, and time series shard, and they are respectively stored in the verification server of the autonomous domain where the current interaction node is located, the buffer area of the next-hop node, and the public timestamp service center; when a complete index is required, verification requests must be sent to the three types of storage sources simultaneously, and each shard can pass the integrity check only when it meets the continuity constraint of the timestamp and the spatial overlap condition of the geographical area.

[0012] As a further solution of the present invention: The geographical positioning shard adopts multiple projection storage, and the coordinate data is simultaneously converted into a dual expression form of the WGS84 coordinate system and the local plane coordinate system; the device feature shard implements feature obfuscation processing, and the original sensor data is blindly convolved with a random noise sequence; the time series shard adopts a difference storage method, and only records the relative time delay between adjacent time nodes instead of the absolute time value; the decryption of the three types of shards requires the combined action of the digital certificate keys of the two interacting parties, the device hardware fingerprint key, and the public timestamp key.

[0013] As a further solution of the present invention: The verification process of the three-dimensional trajectory model includes: establishing a virtual verification channel between any two adjacent nodes, discretizing the trajectory model of the section between the two adjacent nodes into several detection points, and each detection point needs to meet the outbound constraint conditions of the previous node and the inbound constraint conditions of the next node at the same time; the outbound constraint conditions include the data packet length change threshold, the transmission delay fluctuation range, and the signal strength attenuation gradient; the inbound constraint conditions include the checksum matching degree, the packet header structure integrity degree, and the load distribution balance degree; when the detection point meets the two-way constraints at the same time, the trajectory of this section is marked as a trusted path.

[0014] As a further solution of the present invention: the method for dynamically establishing the virtual verification channel is as follows: when a new network topology connection is detected during the data flow process, a candidate verification channel set is automatically generated, and each candidate channel is weighted and scored according to its historical verification passing rate, path redundancy, and node reputation value; the three candidate channels with the highest scores are selected to establish temporary verification links in parallel, and verification operations are synchronously executed when the data flows through. Only when the verification results of at least two temporary channels are consistent, the corresponding section trajectory model is marked as a valid path, and the verification results are fed back to the upstream node to update its reputation value.

[0015] Advantages of the present invention: The present invention solves the problems of the existing data circulation supervision, such as the static identification being difficult to adapt to dynamic changes, the ex post audit being lagged, the lack of environmental perception, and the difficulty in cross-domain path tracing, by establishing a dynamic identification system, setting up environmental perception nodes, and adopting a series of innovative technologies. The dynamic identifier is synthesized by the data content feature value, the interaction timestamp, and the target recipient identity code and updated in a chain, adapting to the dynamic interaction characteristics of the data and ensuring that the data transfer status is accurately reflected in real time. The environmental perception node collects the network topology state, the physical position offset of the device, and the electromagnetic characteristic parameters of the transmission medium to generate an environmental fingerprint data packet, which is asynchronously bound to the dynamic identifier to form a supervision index, realizing the effective perception of the data interaction environment. When cross-domain circulation occurs, the supervision index is reversely analyzed to reconstruct the three-dimensional trajectory model, which can accurately trace the data circulation path. In the generation of the dynamic identifier, the elliptic curve function non-linear mapping and the exclusive OR operation are adopted for updating, ensuring the uniqueness and dynamics of the identifier. The environmental fingerprint data packet generation synthesizes the multi-axis motion sensor data and the wireless access point signal strength matrix, and extracts the characteristic frequency band energy distribution map through wavelet transform, making the data more comprehensive and accurate. The asynchronous binding generates a positioning hash value and a physical feature mark, which are spliced into a verification chain and stored in a distributed manner, enhancing the security and traceability of the supervision index. The three-dimensional trajectory model reconstruction combines the geographical coordinates, the motion correlation coefficient, and the network topology data, and generates a dynamically scalable trajectory through the trace line tracking algorithm, realizing traceability throughout the life cycle. The distributed storage of the verification chain adopts the sharding redundancy strategy and various storage and encryption methods to ensure the integrity and security of the data. The three-dimensional trajectory model verification establishes a virtual verification channel and dynamically selects it to ensure the credibility of the data circulation path and improve the efficiency and accuracy of data circulation supervision. Description of the Drawings

[0016] The present invention will be further described below with reference to the accompanying drawings.

[0017] Figure 1 It is a flow diagram of the present invention. Detailed Embodiments

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0019] Please refer to Figure 1 As shown, the present invention is a method for supervising circulation data based on data interaction, including the following steps: In the process of data flow, constructing a dynamic identification system is the key foundation. At the moment when each data unit initiates an interaction, a unique dynamic identifier will be generated. Its generation process is based on three core elements: the data content feature value, the interaction timestamp, and the target recipient identity code, and is synthesized through a one-way conversion algorithm. Among them, the data content feature value is extracted from the binary sequence of the data unit to generate key information, representing the internal characteristics of the data; the interaction timestamp accurately records the moment when the interaction occurs, giving time dimension information; the target recipient identity code determines the target object of data transmission. Moreover, as the data continuously interacts between different nodes, the dynamic identifier will undergo an irreversible chain update, and each update carries new interaction information, just like the "digital footprint" of data circulation, ensuring that the data can be accurately identified and traced throughout the entire circulation life cycle.

[0020] On the circulation path, the setting of environmental perception nodes provides rich environmental data for supervision work. These nodes will collect multi-dimensional information in real time. Among them, the network topology state reflects the connection structure and changes of the network during data transmission; the device physical position offset records the movement trajectory of the device in space; the electromagnetic characteristic parameters of the transmission medium capture the electromagnetic characteristics of the data transmission medium. Through the comprehensive processing of this information, an environmental fingerprint data packet is generated, which is like the "digital portrait" of the data interaction environment. Subsequently, the dynamic identifier is asynchronously bound to the environmental fingerprint data packet. This binding is not simply a data combination, but a spatio-temporal correlation is established through a specific algorithm to form a supervision index. This index integrates the data itself information and the interaction environment information, providing a complete and associated data basis for subsequent supervision.

[0021] When a data unit undergoes cross - domain circulation, it enters the reconstruction stage of the data circulation path. At this time, by reverse - parsing the environmental fingerprint data packet in the supervision index and using various environmental information contained in the data packet, combined with spatial analysis and data - processing technologies, the transmission path of the data between different regions is gradually restored. Finally, a three - dimensional trajectory model of the data circulation path is constructed. This model presents the entire picture of data circulation in an intuitive and three - dimensional way. It can not only show the path direction of the data from the starting point to the end point, but also reflect the interaction status of the data at different time and space nodes, realizing all - round and visual supervision of data cross - domain circulation.

[0022] During the generation of the dynamic identifier, when the data unit is ready to be sent, the system extracts the check values of bytes at fixed intervals in its binary sequence as the data content feature values to represent the core content attributes of the data. The difference between the local clock of the sender and the standard time source is calculated and processed as the timestamp correction factor to eliminate the time - recording error caused by clock deviation and ensure the accuracy of time information. The receiver identity code uses the truncated hash value of its hardware device's unique identification code, reducing the risk of identity information leakage while ensuring the uniqueness of the identity identification. The above three are input into the elliptic curve function for non - linear mapping. Utilizing the high security and mathematical properties of elliptic curve encryption, the initial dynamic identifier is generated. During subsequent data forwarding, the last - byte of the previous identifier is XOR - operated with the identity code of the new receiver, and the operation result is inserted into the header of the identifier to achieve the chained update of the dynamic identifier. This update mechanism enables the identifier to continuously record new interaction information as the data interacts between different nodes, ensuring that the data can be accurately identified and traced throughout the entire circulation process.

[0023] The generation of the environmental fingerprint data packet depends on multi - source data acquisition and fusion - processing technologies. Multi - axis motion sensors are deployed at the physical devices where data interactions occur. These sensors can continuously monitor the changes in the three - dimensional acceleration and angular velocity of the devices. When a data - transmission instruction is detected, the system automatically records the motion - trajectory waveforms within a set time window before and after the interaction, capturing the physical motion characteristics of the device during data transmission. At the same time, the signal - strength matrix of the wireless access point where the device is located is collected, and the phase offset of each channel carrier frequency is extracted to obtain detailed parameters of the wireless transmission environment. The motion - trajectory waveforms and the phase offsets are aligned in the time domain to ensure the consistency of the two types of data in the time dimension. Subsequently, wavelet - transform technology is used to extract the energy distribution map of the characteristic frequency band from the aligned data. This distribution map is quantified into a multi - dimensional vector and appended with the geographical fence coordinates of the device, thus forming the basic data layer of the environmental fingerprint, which completely records the physical and network environment information during data interaction.

[0024] The asynchronous binding process aims to establish an effective association between dynamic identifiers and environmental fingerprint data packets. After the data unit completes the interactive transmission, the system splits the dynamic identifier into a header verification segment and a tail check segment. The header verification segment performs spatial encoding conversion with the device's geographical coordinates in the environmental fingerprint data packet, generates a positioning hash value through a specific encoding algorithm, and establishes the correspondence between data identification and geographical location; the tail check segment performs a convolution operation with the waveform features collected by the motion sensor to generate a physical feature marker, realizing the binding of data identification and device motion characteristics. The positioning hash value and the physical feature marker are spliced in the order of transmission time to form a verification chain for the supervision index. To ensure data security and traceability, this verification chain adopts a distributed storage method and is split and saved to storage nodes in different geographical regions in the data interaction path. This storage method not only improves data security but also facilitates quick retrieval and verification of data when needed.

[0025] The reconstruction of the three-dimensional trajectory model is based on the in-depth analysis of the supervision index and multi-source data fusion. Extract the positioning hash values corresponding to each interaction from the supervision index, restore the geographical coordinate sequence of the device through the inverse spatial encoding algorithm, and determine the spatial position information during the data transmission process. At the same time, analyze the waveform parameters in the physical feature marker, calculate the motion correlation coefficient between adjacent nodes, and clarify the motion relationship of the device between different nodes. Combining the network topology state data, establish a surface model of the data propagation path in the geographical coordinate system. This model visually presents the data propagation path in the form of a mathematical surface. On the basis of the surface model, superimpose the device motion vector field, and through the streamline tracking algorithm in fluid mechanics, generate a three-dimensional circulation trajectory including time and space dimensions. This trajectory model supports dynamic zoom display along the time axis. Supervisors can view the circulation trajectory of data at different time scales according to needs, realizing all-round visual supervision of data circulation.

[0026] The distributed storage of the verification chain adopts a sharding redundancy strategy to enhance the security and integrity of data storage. Each supervision index is split into three parts: a geographical positioning shard, a device feature shard, and a time series shard. The geographical positioning shard is stored in the verification server of the autonomous domain where the current interaction node is located, the device feature shard is stored in the buffer area of the next-hop node, and the time series shard is stored in the public timestamp service center. When obtaining the complete index, verification requests must be sent to all three types of storage sources simultaneously, and each shard needs to meet the continuity constraint of timestamps and the spatial overlap condition of geographical regions to pass the integrity check. This storage and verification mechanism effectively prevents data from being tampered with or lost during storage and transmission, ensuring data integrity and availability.

[0027] In terms of data storage security, geolocation sharding adopts a multiple projection storage technology, which converts coordinate data into a dual representation form of the WGS84 coordinate system and the local plane coordinate system simultaneously to meet the usage requirements of coordinate data in different scenarios. Device feature sharding implements feature obfuscation processing. By performing blind convolution on the original sensor data and a random noise sequence, the true features of the data are hidden to prevent the risks brought by data leakage. Time series sharding adopts a differential storage method, which only records the relative time delays between adjacent time nodes instead of absolute time values. While ensuring the continuity of the time series, the data storage volume is reduced. The decryption processes of the three shards need to use the digital certificate keys of both communicating parties, the device hardware fingerprint keys, and the public timestamp keys together to form a multi-level encryption protection system to ensure data security.

[0028] The verification process of the three-dimensional trajectory model is achieved by establishing a virtual verification channel. A virtual verification channel is constructed between any two adjacent nodes, and the trajectory model of the section between the two adjacent nodes is discretized into several detection points. Each detection point needs to meet both the outbound constraint conditions of the previous node and the inbound constraint conditions of the next node. The outbound constraint conditions include indicators such as the threshold of packet length change, the fluctuation range of transmission delay, and the attenuation gradient of signal strength to ensure that the data complies with the transmission specifications when leaving the station; the inbound constraint conditions cover requirements such as the checksum matching degree, the integrity of the packet header structure, and the load distribution balance to ensure the integrity and availability of the data when entering the station. When the detection point meets both two-way constraint conditions, the trajectory of this section is marked as a trusted path, effectively screening out abnormal paths and ensuring the credibility of the data circulation path.

[0029] The dynamic establishment mechanism of the virtual verification channel further optimizes the verification process. When a new network topology connection is detected during the data flow process, the system automatically generates a set of candidate verification channels. Each candidate channel is weighted and scored according to indicators such as its historical verification passing rate, path redundancy, and node reputation value. The three candidate channels with the highest scores are selected to establish temporary verification links in parallel, and the verification operations are synchronously executed when the data flows through these temporary links. Only when the verification results of at least two temporary channels are consistent, the trajectory model of the corresponding section is marked as a valid path, and the verification result is feedback to the upstream node for updating its node reputation value. This dynamic establishment and verification mechanism not only improves the verification efficiency but also, through the update of the node reputation value, encourages nodes to maintain the accuracy and security of data transmission, forming a virtuous data circulation supervision ecosystem.

[0030] The above has described a specific embodiment of the present invention in detail, but the described content is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the scope covered by the patent of the present invention.

Claims

1. A circulation data supervision method based on data interaction, characterized in that: The following steps are involved: A dynamic identification system is established during the data circulation process. Each data unit generates a unique dynamic identifier when initiating an interaction. The identifier is synthesized by the data content feature value, the interaction timestamp, and the target recipient identity code through a one-way conversion algorithm. The dynamic identifier is irreversibly chained and updated with each data interaction behavior. Set up environmental perception nodes in the circulation path to collect the network topology status, device physical location offset, and transmission medium electromagnetic characteristic parameters in real time when data interaction occurs, and generate environmental fingerprint data packets; asynchronously bind dynamic identifiers to environmental fingerprint data packets to form a regulatory index with temporal and spatial correlation; When data units flow across domains, the three-dimensional trajectory model of the data flow path is reconstructed by reverse parsing the environmental fingerprint data packet in the regulatory index.

2. A circulation data supervision method based on data interaction according to claim 1, characterized in that: The generation process of the dynamic identifier specifically includes: When a data unit is ready to be sent, the checksum of the fixed-interval bytes in its binary sequence is extracted as the content feature value, the difference between the sender's local clock and the standard time source is used as the timestamp correction factor, and the receiver's identity code uses the truncated hash value of the unique identification code of its hardware device; the three are input into the elliptic curve function for nonlinear mapping to generate an initial dynamic identifier; in each subsequent forwarding, the last byte of the previous identifier is XORed with the identity code of the new recipient, and the result of the operation is inserted into the identifier header to form an updated dynamic identifier chain.

3. A circulation data supervision method based on data interaction according to claim 2, characterized in that: The generation of the environmental fingerprint data packet includes the following steps: Multi-axis motion sensors are deployed at the physical devices where data interaction occurs to continuously monitor the three-dimensional acceleration and angular velocity changes of the device. When a data transmission instruction is detected, the motion trajectory waveform within the set time window before and after the interaction is recorded. At the same time, the signal strength matrix of the wireless access point where the device is located is collected to extract the phase offset of the carrier frequency of each channel. After aligning the motion trajectory waveform and the phase offset in the time domain, the wavelet transform is used to extract the energy distribution map of the characteristic frequency band, which is quantified into a multi-dimensional vector and attached with the geographic fence coordinates of the device to form the basic data layer of the environmental fingerprint.

4. A circulation data supervision method based on data interaction according to claim 3, characterized in that: The asynchronous binding process is specifically as follows: after the data unit completes the interactive transmission, the dynamic identifier is split into a head verification segment and a tail verification segment, the head verification segment is spatially encoded and converted with the device geographic coordinates in the environmental fingerprint data packet to generate a positioning hash value; the tail verification segment is convolved with the waveform features collected by the motion sensor to generate a physical feature tag; The positioning hash value and the physical feature mark are spliced ​​in the order of transmission time to form a verification chain of the regulatory index, which is divided and saved in a distributed storage manner to storage nodes in different geographical areas in the interaction path.

5. The method for monitoring circulation data based on data interaction according to claim 1, characterized in that: The reconstruction method of the three-dimensional trajectory model includes: extracting the positioning hash value corresponding to each interaction from the supervision index, and restoring the geographic coordinate sequence of the device through inverse space coding; simultaneously parsing the waveform parameters in the physical feature mark, and calculating the motion correlation coefficient between adjacent nodes; combining the network topology state data, establishing a propagation path surface model based on the geographic coordinate system, superimposing the device motion vector field on the surface model, and generating a three-dimensional circulation trajectory through a fluid mechanics trace tracking algorithm. The trajectory model can be dynamically scaled and displayed along the time axis.

6. A circulation data supervision method based on data interaction according to claim 4, characterized in that: The distributed storage of the verification chain adopts a sharding redundancy strategy, splitting each regulatory index into three parts: geolocation sharding, device feature sharding, and time series sharding, which are stored in the verification server of the autonomous domain where the current interactive node is located, the cache area of ​​the next hop node, and the public timestamp service center respectively; When a complete index is required, verification requests must be initiated to the three types of storage sources at the same time. Each shard must meet the continuity constraints of the timestamp and the spatial overlap conditions of the geographic area to pass the integrity check.

7. A circulation data supervision method based on data interaction according to claim 6, characterized in that: The geolocation slices are stored using multiple projections to convert coordinate data into dual expressions of WGS84 coordinate system and local plane coordinate system at the same time; The device feature sharding implements feature obfuscation processing, blindly convolving the original sensor data with the random noise sequence; the time series sharding adopts the difference storage method, only recording the relative delay of adjacent time nodes rather than the absolute time value; the decryption of the three shards requires the use of the digital certificate keys of the interacting parties, the device hardware fingerprint key and the public timestamp key.

8. The method for monitoring circulation data based on data interaction according to claim 1, characterized in that: The verification process of the three-dimensional trajectory model includes: A virtual verification channel is established between any two adjacent nodes, and the trajectory model of the segment between the two adjacent nodes is discretized into several detection points. Each detection point must simultaneously meet the outbound constraint conditions of the previous node and the inbound constraint conditions of the next node; the outbound constraint conditions include the packet length change threshold, the transmission delay fluctuation range, and the signal strength attenuation gradient; the inbound constraint conditions include the verification and matching degree, the packet header structure integrity, and the load distribution balance; when the detection point satisfies the bidirectional constraints at the same time, the segment trajectory is marked as a trusted path.

9. A circulation data supervision method based on data interaction according to claim 8, characterized in that: The dynamic establishment method of the virtual verification channel is: When a new network topology connection is detected during data flow, a set of candidate verification channels is automatically generated. Each candidate channel is weighted and scored based on its historical verification pass rate, path redundancy, and node reputation value. The three candidate channels with the highest scores are selected to establish temporary verification links in parallel, and verification operations are performed synchronously when data flows through. Only when the verification results of at least two temporary channels are consistent, the corresponding segment trajectory model is marked as a valid path, and the verification results are fed back to the upstream node to update its reputation value.

Images