A circulation data supervision method based on data interaction

Abstract

The present invention discloses a circulation data supervision method based on data interaction, which belongs to the field of data supervision technology and specifically comprises: establishing a dynamic identification system in the process of data circulation, wherein each data unit generates a unique dynamic identifier when initiating an interaction, and the dynamic identifier is irreversibly chain-updated with each data interaction behavior; setting an environmental perception node in the circulation path, collecting the network topology state, device physical position offset, and transmission medium electromagnetic characteristic parameters when the data interaction occurs in real time, and generating an environmental fingerprint data packet; asynchronously binding the dynamic identifier with the environmental fingerprint data packet to form a supervision index with time-space correlation; when the data unit circulates across domains, reconstructing a three-dimensional trajectory model of the data circulation path by reverse parsing the environmental fingerprint data packet in the supervision index; the present invention improves the efficiency and accuracy of data circulation supervision.

Description

Technical Field

[0001] The present invention relates to the technical field of data supervision, and in particular to a circulation data supervision method 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 subjects and systems has become the norm.

[0003] Currently, data circulation supervision primarily relies on a combination of static identification and post-audit. Static identification typically assigns fixed labels to data at the time of generation, making it difficult to adapt to changes in data characteristics during dynamic interactions. Post-audit relies on manual or simple log analysis, requiring significant manpower and time costs and subject to regulatory lags. Furthermore, while some regulatory methods have introduced the concept of dynamic identification, they struggle to accurately track the actual path of data when it circulates across domains, and lack effective perception and documentation of the network and physical environments in which the data resides.

[0004] Existing data circulation supervision technologies have many shortcomings. Static identification methods cannot accurately reflect the flow status of data in real time when faced with complex and changeable data interaction scenarios. The lack of effective perception of the data interaction environment makes it difficult to build a complete and accurate circulation track when data circulates across domains, and cannot meet the current data security supervision requirements for traceability and verifiability of data throughout its life cycle. Summary of the Invention

[0005] The purpose of the present invention is to provide a circulation data supervision method based on data interaction to solve the following technical problems:

[0006] Static identification methods cannot accurately reflect the flow status of data in real time when faced with complex and changeable data interaction scenarios; and the lack of effective perception of the data interaction environment makes it difficult to construct a complete and accurate circulation track when data circulates across domains.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A circulation data supervision method based on data interaction includes the following steps:

[0009] A dynamic identification system is established during the data circulation process. Each data unit generates a unique dynamic identifier when an interaction is initiated. This identifier is synthesized by the data content feature value, the interaction timestamp, and the target recipient's identity code through a one-way conversion algorithm. The dynamic identifier is irreversibly chained and updated with each data interaction behavior.

[0010] Setting up environmental sensing nodes in the circulation path to collect real-time network topology status, device physical location offset, and transmission medium electromagnetic characteristic parameters when data interaction occurs, and generate environmental fingerprint data packets; asynchronously binding dynamic identifiers to environmental fingerprint data packets to form a regulatory index with temporal and spatial correlation;

[0011] 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 packets in the regulatory index.

[0012] As a further solution of the present invention: the process of generating the dynamic identifier specifically includes:

[0013] When a data unit is ready to be sent, the check value 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 its hardware device's unique identification code; 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.

[0014] As a further solution of the present invention: the generation of the environmental fingerprint data packet includes the following steps:

[0015] Multi-axis motion sensors are deployed at the physical devices where data interaction occurs to continuously monitor the device's three-dimensional acceleration and angular velocity changes. 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 each channel carrier frequency. After aligning the motion trajectory waveform and the phase offset in the time domain, 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 device's geographic fence coordinates to form the basic data layer of the environmental fingerprint.

[0016] As a further solution of the present invention: the asynchronous binding process is specifically as follows: after the data unit completes the interactive transmission, the dynamic identifier is split into a header verification segment and a tail check segment, the header 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 check 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 tag are spliced ​​in the order of transmission time to form a verification chain of the supervision index, and the verification chain is divided and saved in a distributed storage manner to storage nodes in different geographical areas in the interactive path.

[0017] As a further solution of the present invention: 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 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 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.

[0018] As a further solution of the present invention: the distributed storage of the verification chain adopts a sharding redundancy strategy, splitting each regulatory index into three parts: geolocation shard, device feature shard, and time series shard, which are respectively 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; when a complete index is required, a verification request must be initiated to the three types of storage sources at the same time, and each shard must meet the continuity constraint of the timestamp and the spatial overlap condition of the geographical area to pass the integrity check.

[0019] As a further solution of the present invention: the geolocation slice adopts multi-projection storage to convert the coordinate data into dual expressions of the WGS84 coordinate system and the local plane coordinate system at the same time; the device feature slice implements feature obfuscation processing to blindly convolve the original sensor data with the random noise sequence; the time series slice adopts the difference storage method to only record the relative delay of adjacent time nodes rather than the absolute time value; the decryption of the three slices requires the use of the digital certificate key of the interacting parties, the device hardware fingerprint key and the public timestamp key.

[0020] 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 segment between the two adjacent nodes into a number of checkpoints, each of which must simultaneously meet the outbound constraints of the previous node and the inbound constraints of the next node. The outbound constraints include the packet length change threshold, the transmission delay fluctuation range, and the signal strength attenuation gradient; the inbound constraints include the checksum matching degree, the packet header structure integrity, and the load distribution balance. When a checkpoint simultaneously meets the two-way constraints, the trajectory segment is marked as a trusted path.

[0021] As a further solution of the present invention: the dynamic establishment method of the virtual verification channel is: when a new network topology connection is detected during the data flow process, a set of candidate verification channels is automatically generated, and each candidate channel is weighted and scored according to 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.

[0022] Beneficial effects of the present invention:

[0023] This invention addresses existing issues of static identifiers used for data flow supervision, such as difficulty adapting to dynamic changes, delayed post-audits, a lack of environmental awareness, and difficulty in cross-domain path tracking, by establishing a dynamic identification system, setting up environmental awareness nodes, and employing a series of innovative technologies. The dynamic identifier is synthesized and updated in a chain, adapting to the dynamic interaction characteristics of data and ensuring real-time and accurate reflection of data flow status. The environmental awareness node collects network topology, device physical position offset, and transmission medium electromagnetic characteristics to generate an environmental fingerprint data packet. This data packet is asynchronously bound to the dynamic identifier to form a regulatory index, effectively perceiving the data interaction environment. During cross-domain data flow, the regulatory index is reversely parsed to reconstruct a three-dimensional trajectory model, enabling precise tracking of data flow paths. Elliptic curve functions are used for nonlinear mapping and XOR operation updates to ensure uniqueness and dynamic identity. The environmental fingerprint data packet generates integrated multi-axis motion sensor data and wireless access point signal strength matrices. Wavelet transforms are used to extract characteristic frequency band energy distribution maps, resulting in more comprehensive and accurate data. Asynchronous binding generates location hash values ​​and physical feature tags, which are then spliced ​​into a verification chain and distributedly stored, enhancing the security and traceability of the regulatory index. 3D trajectory model reconstruction combines geographic coordinates, motion correlation coefficients, and network topology data, generating dynamically scalable trajectories through a trace tracking algorithm, enabling full lifecycle traceability. Verification chain distributed storage utilizes a sharding redundancy strategy and multiple storage and encryption methods to ensure data integrity and security. 3D trajectory model verification establishes and dynamically selects virtual verification channels to ensure the trustworthiness of data flow paths and improve the efficiency and accuracy of data flow supervision. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present invention will be further described below with reference to the accompanying drawings.

[0025] Figure 1 It is a schematic flow diagram of the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0027] See also Figure 1 As shown, the present invention is a circulation data supervision method based on data interaction, comprising the following steps:

[0028] In the process of data circulation, building a dynamic identification system is the key foundation. Each data unit will generate a unique dynamic identifier at the moment of initiating interaction. Its generation process is based on three core elements: data content characteristic value, interaction timestamp, and target recipient identity code, and is synthesized through a one-way conversion algorithm. Among them, the data content characteristic value is generated by extracting key information from the binary sequence of the data unit, representing the intrinsic characteristics of the data; the interaction timestamp accurately records the moment when the interaction occurs and gives time dimension information; the target recipient identity code determines the target object of the data transmission. Moreover, as data continues to interact between different nodes, the dynamic identifier will produce irreversible chain updates. Each update carries new interaction information, like a "digital footprint" of data flow, ensuring that data can be accurately identified and tracked throughout its circulation life cycle.

[0029] Along the circulation path, the deployment of environmental sensing nodes provides a wealth of environmental data for regulatory oversight. These nodes collect multi-dimensional information in real time. Network topology reflects the network's connectivity structure and changes during data transmission; device physical position offsets record the device's movement trajectory in space; and transmission medium electromagnetic characteristics capture the electromagnetic properties of the data transmission medium. This information is comprehensively processed to generate an environmental fingerprint data packet, a "digital portrait" of the data interaction environment. Subsequently, a dynamic identifier is asynchronously bound to the environmental fingerprint data packet. This binding is not a simple data combination; rather, it establishes spatiotemporal correlations through a specific algorithm, forming a regulatory index. This index integrates the data itself with information about the interaction environment, providing a complete and relevant data foundation for subsequent oversight.

[0030] When data units circulate across domains, the data flow path reconstruction phase begins. At this point, by reverse-analyzing the environmental fingerprint data packets in the regulatory index and utilizing the various environmental information contained in the data packets, combined with spatial analysis and data processing techniques, the data transmission paths between different regions are gradually restored. Ultimately, a three-dimensional trajectory model of the data flow path is constructed. This model presents the entire data flow in an intuitive and three-dimensional manner. It not only shows the path of the data from its starting point to its end point, but also reflects the interactive status of the data at different time and space nodes, enabling comprehensive and visual supervision of cross-domain data flow.

[0031] During the dynamic identifier generation process, when a data unit is ready to be sent, the system extracts the checksum of regularly spaced bytes in its binary sequence as a data content feature value, thereby characterizing the core content attributes of the data. The difference between the sender's local clock and a standard time source is calculated and processed as a timestamp correction factor to eliminate time recording errors caused by clock deviation and ensure the accuracy of time information. The recipient's identity code uses a truncated hash value of the unique identification code of their hardware device, ensuring uniqueness while reducing the risk of identity leakage. These three factors are input into an elliptic curve function for nonlinear mapping, leveraging the high security and mathematical properties of elliptic curve cryptography to generate an initial dynamic identifier. During subsequent data forwarding, the last byte of the previous identifier is XORed with the new recipient's identity code, and the result is inserted into the identifier header, implementing a chained update of the dynamic identifier. This update mechanism enables the identifier to continuously record new interaction information as data moves between different nodes, ensuring accurate identification and traceability throughout the data flow.

[0032] The generation of environmental fingerprint data packets relies on multi-source data acquisition and fusion processing technology. Multi-axis motion sensors are deployed at the physical devices where data exchange occurs. These sensors continuously monitor the device's three-dimensional acceleration and angular velocity changes. When a data transmission instruction is detected, the system automatically records the motion trajectory waveform within a set time window before and after the exchange, capturing the device's physical motion characteristics during the data transmission process. Simultaneously, the signal strength matrix of the wireless access point where the device is located is collected, and the phase offset of each channel's carrier frequency is extracted to obtain detailed parameters of the wireless transmission environment. The motion trajectory waveform and phase offset are aligned in the time domain to ensure consistency between the two types of data in the temporal dimension. Wavelet transform technology is then used to extract the energy distribution map of the characteristic frequency band from the aligned data. This distribution map is quantized into a multidimensional vector and appended with the device's geofence coordinates, forming the basic data layer of the environmental fingerprint, which fully records the physical and network environment information during the data exchange.

[0033] The asynchronous binding process aims to establish an effective association between the dynamic identifier and the environmental fingerprint data packet. 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 is spatially encoded with the device's geographic coordinates in the environmental fingerprint data packet, and a positioning hash value is generated through a specific encoding algorithm to establish a correspondence between the data identifier and the geographic location. The tail check segment is convolved with the waveform characteristics collected by the motion sensor to generate a physical feature tag, thereby binding the data identifier to the device's motion characteristics. The positioning hash value and the physical feature tag are spliced ​​in the order of transmission time to form a verification chain of the regulatory index. To ensure data security and traceability, this verification chain uses a distributed storage method, splitting the storage to storage nodes in different geographical areas along the data interaction path. This storage method not only improves data security but also facilitates rapid retrieval and verification of data when needed.

[0034] The reconstruction of the three-dimensional trajectory model is based on in-depth analysis of the regulatory index and fusion of multi-source data. The positioning hash value corresponding to each interaction is extracted from the regulatory index, and the geographic coordinate sequence of the device is restored through the inverse spatial coding algorithm to determine the spatial location information during the data transmission process. At the same time, the waveform parameters in the physical feature markers are analyzed, the motion correlation coefficient between adjacent nodes is calculated, and the motion relationship between devices at different nodes is clarified. Combined with the network topology status data, a surface model of the data propagation path is established in the geographic coordinate system. This model intuitively presents the data propagation path in the form of a mathematical surface. On the basis of the surface model, the device motion vector field is superimposed, and the trace tracking algorithm in fluid mechanics is used to generate a three-dimensional circulation trajectory containing time and space dimensions. The trajectory model supports dynamic scaling display along the time axis. Supervisors can view the data circulation trajectory at different time scales as needed, realizing all-round visual supervision of data circulation.

[0035] The distributed storage of the verification chain adopts a sharding redundancy strategy to improve the security and integrity of data storage. Each regulatory index is split into three parts: geolocation shard, device feature shard, and time series shard. The geolocation shard is stored in the verification server of the autonomous domain where the current interactive node is located, the device feature shard is stored in the cache area of ​​the next-hop node, and the time series shard is stored in the public timestamp service center. When a complete index is required, a verification request must be initiated to all three types of storage sources at the same time, and each shard must meet the timestamp continuity constraints and the spatial overlap conditions of the geographic area in order 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.

[0036] In terms of data storage security, geolocation sharding uses multi-projection storage technology to convert coordinate data into dual expressions of the WGS84 coordinate system and the local plane coordinate system to accommodate the use of coordinate data in different scenarios. Device feature sharding implements feature obfuscation processing by blindly convolving the raw sensor data with a random noise sequence to hide the true characteristics of the data and prevent the risk of data leakage. Time series sharding uses a differential storage method, recording only the relative delays between adjacent time nodes rather than absolute time values. This reduces data storage while ensuring the continuity of the time series. The decryption process of the three shards requires the interaction of the digital certificate keys of the interacting parties, the device hardware fingerprint key, and the public timestamp key to form a multi-level encryption protection system to ensure data security.

[0037] 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 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 indicators such as the packet length change threshold, the transmission delay fluctuation range, and the signal strength attenuation gradient to ensure that the data meets the transmission specifications when it leaves the station; the inbound constraint conditions cover requirements such as verification and matching, packet header structure integrity, and load distribution balance to ensure the integrity and availability of the data when it enters the station. When the detection point meets the two-way constraint conditions at the same time, the segment trajectory is marked as a trusted path, thereby effectively screening out abnormal paths and ensuring the credibility of the data flow path.

[0038] The dynamic establishment mechanism of virtual verification channels further optimizes the verification process. When a new network topology connection is detected during data circulation, the system automatically generates a set of candidate verification channels. Each candidate channel is weighted and scored based on its historical verification pass rate, path redundancy, node reputation value and other indicators. 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 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 results are fed back to the upstream node to update its node reputation value. This dynamic establishment and verification mechanism not only improves verification efficiency, but also incentivizes nodes to maintain the accuracy and security of data transmission through the update of node reputation values, forming a benign data circulation supervision ecosystem.

[0039] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage 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 an interaction is initiated. This identifier is synthesized by the data content feature value, the interaction timestamp, and the target recipient's identity code through a one-way conversion algorithm. The dynamic identifier is irreversibly chained and updated with each data interaction behavior. Setting up environmental sensing nodes in the circulation path to collect real-time network topology status, device physical location offset, and transmission medium electromagnetic characteristic parameters when data interaction occurs, and generate environmental fingerprint data packets; asynchronously binding dynamic identifiers to environmental fingerprint data packets to form a regulatory index with temporal and spatial correlation; When data units are circulated across domains, the three-dimensional trajectory model of the data flow path is reconstructed by reverse parsing the environmental fingerprint data packets in the regulatory index; The verification process of the three-dimensional trajectory model includes: A virtual verification channel is established between any two adjacent nodes. 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 constraints of the previous node and the inbound constraints of the next node. The outbound constraints include the packet length change threshold, transmission delay fluctuation range, and signal strength attenuation gradient. The inbound constraints include the checksum matching degree, packet header structure integrity, and load distribution balance. When a detection point satisfies both bidirectional constraints, the segment trajectory is marked as a trusted path. 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.

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 check value 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 its hardware device's unique identification code; 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 device's three-dimensional acceleration and angular velocity changes. 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 each channel carrier frequency. After aligning the motion trajectory waveform and the phase offset in the time domain, 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 device's geographic fence coordinates to form the basic data layer of the environmental fingerprint.

4. A data exchange-based circulation data supervision method 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 check 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 check 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 supervision 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 three-dimensional trajectory model reconstruction method 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 markers and calculating the motion correlation coefficient between adjacent nodes; combining network topology status data to establish 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. The method for monitoring circulation data 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 shard, device feature shard, and time series shard. These are stored in the verification server of the autonomous domain where the current interaction 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 timestamp continuity constraints and the spatial overlap conditions of the geographical area to pass the integrity check.

7. The method for monitoring circulation data 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 the WGS84 coordinate system and the local plane coordinate system; Device feature sharding implements feature obfuscation processing, blindly convolving the original sensor data with a random noise sequence; time series sharding adopts a difference storage method, recording only the relative delays of adjacent time nodes rather than absolute time values; the decryption of the three types of shards requires the joint use of the digital certificate keys of the interacting parties, the device hardware fingerprint key, and the public timestamp key.

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