Distributed data transmission method, transmitting end, receiving end, equipment and medium

Abstract

The invention discloses a distributed data transmission method, a sending end, a receiving end, equipment and a medium, and belongs to the technical field of data security transmission, the method comprises the following steps: dynamically fragmenting target data to obtain a plurality of sub-data; based on a preset public key and a preset private key, encrypting each piece of sub-data through a quantum encryption function to obtain a plurality of encrypted ciphertexts; performing hybrid calculation on the SHA-3 Hash value, the SM3 Hash value and the SM9 Hash value of each sub-data based on the dynamic Hash weight to obtain a plurality of verification tags; and transmitting the encrypted ciphertexts and the corresponding verification labels to a receiving end in parallel through a distributed node network, so that the receiving end decrypts the encrypted ciphertexts to obtain the sub-data, performing integrity verification by adopting a hierarchical hash tree according to the sub-data and the corresponding verification labels, and when the integrity verification meets a preset condition, sending the verification labels to the receiving end. And recombining to obtain target data. Therefore, by implementing the invention, the security and stability of distributed data transmission can be improved.

Description

Technical Field

[0001] This invention relates to the field of data security transmission technology, and in particular to a distributed data transmission method, a sending end, a receiving end, a device, and a medium. Background Technology

[0002] In distributed data transmission, the reliability of node selection and the dynamic adaptability of routing paths are the core challenges. Existing technologies rely on static node pools and single-dimensional (such as bandwidth or latency) routing algorithms, which do not fully consider real-time node behavior (such as historical reliability or resource utilization) and dynamic network environments (such as congestion or interference).

[0003] Specifically, existing technologies have the following drawbacks: First, there is the risk of node trust issues. If the routing algorithm selects a low-reputation node (such as one with malicious attacks, high packet loss rate, or historical data tampering records), it may lead to data leakage, transmission interruption, or tampering. Once a node loses its reputation, it will disrupt system consistency, and existing solutions lack an effective detection mechanism. Second, routing optimization is based on a single dimension. Existing technologies often use bandwidth or latency as weights without considering security factors such as node reputation or encryption strength. For example, when a core node has high bandwidth but is overloaded or has low reputation, it may still be selected as a path, leading to transmission failure or delay and significantly increasing costs. Summary of the Invention

[0004] This invention provides a distributed data transmission method, a transmitter, a receiver, a device, and a medium, which can improve the security and stability of distributed data transmission.

[0005] This invention provides a distributed data transmission method applicable to the sending end, the distributed data transmission method comprising:

[0006] The target data is dynamically fragmented to obtain multiple sub-data; wherein, the fragment size of the sub-data is adjusted according to the data type, real-time network bandwidth, transmission delay, node load rate and signal-to-noise ratio.

[0007] Based on a preset public key and private key, each of the sub-data is encrypted using a quantum encryption function to obtain multiple encrypted ciphertexts; wherein, the private key is dynamically updated based on a quantum random number generator and a timestamp, and the public key is used for signature verification based on the Chinese national cryptographic SM9 algorithm;

[0008] Based on dynamic hash weights, the SHA-3 hash value, SM3 hash value, and SM9 hash value of each sub-data are mixed and calculated to obtain multiple verification tags; wherein, the dynamic hash weights are allocated according to the data security level;

[0009] Each encrypted ciphertext and its corresponding verification tag are transmitted in parallel to the receiving end through a distributed node network, so that the receiving end can decrypt each encrypted ciphertext to obtain each sub-data. Based on each sub-data and its corresponding verification tag, a hierarchical hash tree is used to perform integrity verification. When the integrity verification meets the preset conditions, the target data is reassembled. The transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism.

[0010] This invention dynamically adjusts the fragment size based on data type and real-time network status, providing a data foundation for efficient distributed data transmission. By employing dynamically updated quantum keys and performing SM9 signature verification, it effectively resists quantum computing attacks and ensures the trustworthiness of the key source. Dynamically mixing multiple hash values ​​to generate verification tags based on security levels enhances the strength of subsequent data integrity verification. A blockchain-based reputation assessment mechanism selects high-reputation nodes for parallel transmission, improving the reliability of routing paths and reducing the risk of transmission failure. Compared to existing technologies that suffer from node trust risks and limited routing optimization, this application improves the security and stability of distributed data transmission.

[0011] Furthermore, the target data is dynamically segmented to obtain multiple sub-data, including:

[0012] Set the base fragment size according to the data type of the target data;

[0013] The dynamic fragmentation coefficient is calculated based on real-time network bandwidth, transmission delay, node load rate, and signal-to-noise ratio.

[0014] The product of the base partition size and the dynamic partition coefficient is used as the partition size, and the target data is dynamically partitioned according to the partition size to obtain multiple sub-data.

[0015] The embodiments of the present invention calculate dynamic fragmentation coefficients based on network bandwidth, latency, load, and signal-to-noise ratio, and determine the final fragmentation size, which enables data fragmentation to adapt to network fluctuations and improves transmission efficiency and stability.

[0016] Furthermore, the transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism, including:

[0017] The reputation score of each node is calculated based on its transmission success rate, response time, resource utilization, and protocol compatibility score within a preset time.

[0018] Nodes with reputation values ​​greater than or equal to a preset reputation threshold are designated as transmission nodes in the distributed node network.

[0019] This invention calculates a reputation value based on node transmission success rate, response time, resource utilization, and protocol compatibility, and then filters high-reputation nodes, which can effectively eliminate unreliable nodes and improve the reliability of the transmission path.

[0020] Furthermore, after transmitting each encrypted ciphertext and corresponding verification tag to the receiving end in parallel via a distributed node network, the method further includes:

[0021] The transmission quality is monitored in real time. When the transmission quality does not meet the preset conditions, the improved Dijkstra routing algorithm is used to dynamically adjust the routing path based on the weight function. The weight function is constructed based on the real-time network bandwidth, transmission delay and reputation value. The weight coefficient corresponding to the reputation value is constructed based on the real-time network congestion level.

[0022] This invention, through real-time monitoring of transmission quality and dynamic route adjustment using an improved Dijkstra algorithm, can optimize the path based on network congestion, latency, and node reputation, thereby reducing end-to-end transmission latency.

[0023] Another embodiment of the present invention provides a distributed data transmission method, applicable to a receiving end, the distributed data transmission method comprising:

[0024] The system receives encrypted ciphertexts and corresponding verification tags transmitted in parallel by the sending end through a distributed node network. The encrypted ciphertexts are obtained by the sending end encrypting each sub-data item using a quantum encryption function based on a preset public and private key. The verification tags are obtained by the sending end performing a mixed calculation on the SHA-3, SM3, and SM9 hash values ​​of each sub-data item based on dynamic hash weights. The sub-data items are obtained by the sending end dynamically fragmenting the target data.

[0025] Decrypt each of the encrypted ciphertexts to obtain the corresponding sub-data;

[0026] Based on each sub-data and its corresponding verification label, a hierarchical hash tree is used for integrity verification.

[0027] When the integrity check meets the preset conditions, the target data is reconstructed.

[0028] The embodiments of the present invention, by receiving and decrypting encrypted ciphertext, and performing integrity verification and reorganization based on verification tags and hierarchical hash trees, can ensure the consistency and integrity of all sub-data in distributed transmission and achieve reliable data recovery.

[0029] Furthermore, the step of performing integrity verification using a hierarchical hash tree based on each of the sub-data and the corresponding verification label includes:

[0030] The verification label of each sub-data is used as the hash value of the leaf node. The first root hash value is generated by calculating the hash value of the parent node layer by layer.

[0031] The first hash value is compared with the second hash value generated by the sending end to obtain the integrity verification result.

[0032] The embodiments of the present invention can efficiently and accurately verify data integrity by comparing the first hash value generated by the receiving end with the second hash value provided by the sending end.

[0033] Another embodiment of the present invention provides a transmitting end, including: a dynamic fragmentation module, a quantum encryption module, a hash verification module, and a data transmission module;

[0034] The dynamic sharding module is used to dynamically shard the target data to obtain multiple sub-data; wherein, the shard size of the sub-data is adjusted according to the data type, real-time network bandwidth, transmission delay, node load rate and signal-to-noise ratio;

[0035] The quantum encryption module is used to encrypt each of the sub-data based on a preset public key and private key using a quantum encryption function, thereby obtaining multiple encrypted ciphertexts; wherein, the private key is dynamically updated based on a quantum random number generator and a timestamp, and the public key is used for signature verification based on the Chinese national cryptographic algorithm SM9;

[0036] The hash verification module is used to perform mixed calculations on the SHA-3 hash value, SM3 hash value and SM9 hash value of each sub-data based on dynamic hash weights, to obtain multiple verification tags; wherein, the dynamic hash weights are allocated according to the data security level;

[0037] The data transmission module is used to transmit each encrypted ciphertext and its corresponding verification tag to the receiving end in parallel through a distributed node network, so that the receiving end can decrypt each encrypted ciphertext to obtain each sub-data, and perform integrity verification using a hierarchical hash tree based on each sub-data and its corresponding verification tag. When the integrity verification meets a preset condition, the target data is reassembled. The transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism.

[0038] Another embodiment of the present invention provides a receiving end, including: a data receiving module, a data decryption module, a data verification module, and a data reassembly module;

[0039] The data receiving module is used to receive each encrypted ciphertext and corresponding verification tag transmitted in parallel by the sending end through a distributed node network; wherein, the encrypted ciphertext is obtained by the sending end encrypting each sub-data using a quantum encryption function based on a preset public key and private key; the verification tag is obtained by the sending end performing mixed calculations on the SHA-3 hash value, SM3 hash value, and SM9 hash value of each sub-data based on dynamic hash weights; the sub-data is obtained by the sending end dynamically fragmenting the target data;

[0040] The data decryption module is used to decrypt each of the encrypted ciphertexts to obtain each of the sub-data.

[0041] The data verification module is used to perform integrity verification using a hierarchical hash tree based on each of the sub-data and the corresponding verification label.

[0042] The data reconstruction module is used to reconstruct the target data when the integrity verification meets the preset conditions.

[0043] Another embodiment of the present invention provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the steps of a distributed data transmission method as described in the present invention.

[0044] Another embodiment of the present invention provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform steps of a distributed data transmission method as described in the present invention. Attached Figure Description

[0045] Figure 1 A flowchart illustrating an embodiment of the distributed data transmission method provided by the present invention;

[0046] Figure 2 A flowchart illustrating another embodiment of the distributed data transmission method provided by the present invention;

[0047] Figure 3 A flowchart illustrating another embodiment of the distributed data transmission method provided by the present invention;

[0048] Figure 4 A schematic diagram of the structure of one embodiment of the transmitting end provided by the present invention;

[0049] Figure 5 This is a schematic diagram of one embodiment of the receiving end provided by the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0052] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0053] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0054] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0055] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0056] See Figure 1 To address the issues of node trust risks and limited routing optimization in existing technologies, an embodiment of the present invention provides a distributed data transmission method applicable to the sending end. The distributed data transmission method includes steps S101 to S104:

[0057] Step S101: Dynamically segment the target data to obtain multiple sub-data; wherein, the segment size of the sub-data is adjusted according to the data type, real-time network bandwidth, transmission delay, node load rate and signal-to-noise ratio.

[0058] Preferably, the dynamic segmentation of the target data to obtain multiple sub-data includes:

[0059] First, set the base shard size according to the data type of the target data.

[0060] In one embodiment, the data types include real-time data, batch data, and sensitive data; wherein, the base fragment size for real-time data (such as video streams or sensor data) can be set to 512KB to ensure low-latency transmission; the base fragment size for batch data (such as log files or documents) can be set to 2MB to balance bandwidth utilization; and the base fragment size for sensitive data (such as financial transactions or medical data) can be set to 256KB to enhance encryption efficiency.

[0061] Second, calculate the dynamic fragmentation coefficient based on real-time network bandwidth, transmission delay, node load rate, and signal-to-noise ratio.

[0062] In one embodiment, the dynamic fragmentation coefficient M can be set using the following formula:

[0063]

[0064] Where B is the real-time network bandwidth; D is the transmission delay; L is the node load rate, where 0 ≤ L ≤ 1; SNR is the signal-to-noise ratio; S0 is the basic fragmentation size; and δ is the load sensitivity coefficient, where 0.1 ≤ δ ≤ 0.3. Specifically, in the calculation of the dynamic fragmentation coefficient, ln(1+SNR) uses the natural logarithm function to ensure that the fragmentation size increases non-linearly with the increase of the signal-to-noise ratio. For example, when the SNR increases from 10dB to 20dB, the increase in fragmentation size is significantly greater than that from 0dB to 10dB, ensuring full utilization of bandwidth in high signal-to-noise ratio environments; δ×L 2 By introducing a quadratic factor, the sensitivity of fragment size to node load increases exponentially.

[0065] Third, the product of the basic partition size and the dynamic partition coefficient is used as the partition size, and the target data is dynamically partitioned according to the partition size to obtain multiple sub-data.

[0066] Step S102: Based on the preset public key and private key, each of the sub-data is encrypted using a quantum encryption function to obtain multiple encrypted ciphertexts; wherein, the private key is dynamically updated based on a quantum random number generator and a timestamp, and the public key is used for signature verification based on the national cryptographic SM9 algorithm.

[0067] In one embodiment, the private key QSK can be dynamically updated using the following formula:

[0068]

[0069] QRNG stands for Quantum Random Number Generator; T S This is the current timestamp; XOR operation; in particular, in the dynamic update of the private key, the XOR operation ensures that even if the randomness of QRNG is insufficient, an unpredictable key can still be generated by combining it with the timestamp; and the periodic change of the timestamp makes the key time-sensitive, avoiding the risk of long-term key reuse.

[0070] In one embodiment, after the sub-data is divided into data blocks, each data block is transmitted using quantum bit encoding (such as polarization state or phase encoding). The public key QPK and private key QSK are transmitted after the quantum state. prev The encrypted ciphertext is obtained by combining the following methods:

[0071] C = QEnc(QPK, Data, QSK) prev );

[0072] Among them, QSK prev This is the hash value of the previous private key, used to prevent key chain break attacks. A feasible approach is for the sender and receiver to exchange non-sensitive information (such as negotiation parameters) through a channel during the key negotiation phase, while simultaneously transmitting the key through a quantum channel. Furthermore, the sender and receiver detect abnormal disturbances in transmission by comparing the results of the basis measurements. If the error rate exceeds a threshold, the current key is discarded and renegotiated.

[0073] Step S103: Based on the dynamic hash weight, the SHA-3 hash value, SM3 hash value and SM9 hash value of each of the sub-data are mixed and calculated to obtain multiple verification tags; wherein, the dynamic hash weight is allocated according to the data security level.

[0074] In one embodiment, dynamic hash weights can be allocated according to the following formula:

[0075]

[0076] w2 = 1 - w1;

[0077] Where w1 is the dynamic hash weight corresponding to the SHA-3 hash value; w2 is the dynamic hash weight corresponding to the SM3 hash value; SL is the security level; k2 is the adjustment coefficient, the value of which can be dynamically adjusted through experiments or existing intelligent algorithms (such as genetic algorithms or particle swarm optimization) to control the speed or sensitivity of the influence of the security level SL on the dynamic hash weight w1. When k2 is larger, w1 is more sensitive to changes in SL.

[0078] In one embodiment, the verification label H can be generated according to the following formula:

[0079]

[0080] Where H1 is the SHA-3 hash value; H2 is the SM3 hash value; H3 is the SM9 hash value; T S This is the current timestamp; This is a bitwise XOR operation; This is an XOR operation.

[0081] Step S104: Each encrypted ciphertext and its corresponding verification tag are transmitted in parallel to the receiving end through a distributed node network, so that the receiving end can decrypt each encrypted ciphertext to obtain each sub-data. Based on each sub-data and its corresponding verification tag, a hierarchical hash tree is used to perform integrity verification. When the integrity verification meets the preset conditions, the target data is reassembled. The transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism.

[0082] Preferably, the transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism, including:

[0083] First, calculate the reputation score of each node based on its transmission success rate, response time, resource utilization, and protocol compatibility score within a preset time.

[0084] In one embodiment, the reputation value R can be calculated according to the following formula:

[0085]

[0086] Where P is the transmission success rate within a preset time period, which can be calculated based on the exponentially weighted moving average (EWMA); T is the response time; T avg U is the moving average of response time over a preset time period; U is the resource utilization rate; U maxTo maximize resource utilization, the maximum value designed for the node hardware can be set (e.g., 95% CPU or 90% memory). Real-time data is collected from the node monitoring module. The PC scores protocol compatibility (0-100). For example, supporting Chinese cryptographic algorithms (SM2 / SM3 / SM9) earns 50 points, compatibility with quantum encryption protocols earns 30 points, and other protocols (e.g., TLS 1.3) add 5 points for each, up to a maximum of 20 points. The score can be recalculated based on protocol version iterations. max The maximum protocol compatibility score is given; k is an adjustment coefficient used to control the speed or sensitivity of the impact of response time T on reputation value R, where k can be the optimal value determined through historical data or simulation tests.

[0087] Second, nodes with reputation values ​​greater than or equal to a preset reputation threshold are designated as transmission nodes in the distributed node network.

[0088] In one embodiment, nodes with reputation values ​​less than a reputation threshold are removed from the routing pool.

[0089] Preferably, after transmitting each encrypted ciphertext and corresponding verification tag to the receiving end in parallel through a distributed node network, the method further includes:

[0090] The transmission quality is monitored in real time. When the transmission quality does not meet the preset conditions, the improved Dijkstra routing algorithm is used to dynamically adjust the routing path based on the weight function. The weight function is constructed based on the real-time network bandwidth, transmission delay and reputation value. The weight coefficient corresponding to the reputation value is constructed based on the real-time network congestion level.

[0091] In one embodiment, the weighting function can be expressed by the following formula:

[0092]

[0093] Where Bandwidth is the real-time network bandwidth (in Mbps); Delay is the transmission delay (in ms); Reputation is the reputation value; α, β, and γ are weighting coefficients, satisfying α + β + γ = 1.

[0094] In one embodiment, the weighting coefficient γ can be calculated according to the following formula:

[0095]

[0096] Where γ0 is the current weight value; C is the real-time network congestion level; C max This represents the maximum network congestion threshold. Specifically, when the weighting coefficient exceeds a preset upper limit, a backup route switching mechanism based on the ant colony algorithm, as used in existing technologies, can be triggered.

[0097] This invention provides a data foundation for efficient distributed data transmission by dynamically adjusting the fragment size based on data type and real-time network status. By employing dynamically updated quantum keys and performing SM9 signature verification, it effectively resists quantum computing attacks and ensures the trustworthiness of the key source. By dynamically mixing multiple hash values ​​to generate verification tags based on security levels, it enhances the strength of subsequent data integrity verification. Furthermore, by using a blockchain-based reputation assessment mechanism to select high-reputation nodes for parallel transmission, it improves the reliability of routing paths and reduces the risk of transmission failure.

[0098] Optionally, in this embodiment of the invention, the dynamic segmentation of the target data to obtain multiple sub-data includes:

[0099] Set the base fragment size according to the data type of the target data;

[0100] The dynamic fragmentation coefficient is calculated based on real-time network bandwidth, transmission delay, node load rate, and signal-to-noise ratio.

[0101] The product of the base partition size and the dynamic partition coefficient is used as the partition size, and the target data is dynamically partitioned according to the partition size to obtain multiple sub-data.

[0102] The embodiments of the present invention calculate dynamic fragmentation coefficients based on network bandwidth, latency, load, and signal-to-noise ratio, and determine the final fragmentation size, which enables data fragmentation to adapt to network fluctuations and improves transmission efficiency and stability.

[0103] Optionally, in this embodiment of the invention, the transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism, including:

[0104] The reputation score of each node is calculated based on its transmission success rate, response time, resource utilization, and protocol compatibility score within a preset time.

[0105] Nodes with reputation values ​​greater than or equal to a preset reputation threshold are designated as transmission nodes in the distributed node network.

[0106] This invention calculates a reputation value based on node transmission success rate, response time, resource utilization, and protocol compatibility, and then filters high-reputation nodes, which can effectively eliminate unreliable nodes and improve the reliability of the transmission path.

[0107] Optionally, in this embodiment of the invention, after transmitting each encrypted ciphertext and the corresponding verification tag to the receiving end in parallel through a distributed node network, the method further includes:

[0108] The transmission quality is monitored in real time. When the transmission quality does not meet the preset conditions, the improved Dijkstra routing algorithm is used to dynamically adjust the routing path based on the weight function. The weight function is constructed based on the real-time network bandwidth, transmission delay and reputation value. The weight coefficient corresponding to the reputation value is constructed based on the real-time network congestion level.

[0109] This invention, through real-time monitoring of transmission quality and dynamic route adjustment using an improved Dijkstra algorithm, can optimize the path based on network congestion, latency, and node reputation, thereby reducing end-to-end transmission latency.

[0110] like Figure 2 As shown, based on the above-described method embodiment, another embodiment of a distributed data transmission method is provided, applicable to the sending end. The distributed data transmission method includes steps S201 to S204:

[0111] Step S201: Receive each encrypted ciphertext and corresponding verification tag transmitted in parallel by the sending end through a distributed node network; wherein, the encrypted ciphertext is obtained by the sending end encrypting each sub-data using a quantum encryption function based on a preset public key and private key; the verification tag is obtained by the sending end performing mixed calculations on the SHA-3 hash value, SM3 hash value, and SM9 hash value of each sub-data based on dynamic hash weights; the sub-data is obtained by the sending end dynamically fragmenting the target data.

[0112] Step S202: Decrypt each of the encrypted ciphertexts to obtain the corresponding sub-data.

[0113] Step S203: Based on each of the sub-data and the corresponding verification label, perform integrity verification using a hierarchical hash tree.

[0114] Preferably, the step of performing integrity verification using a hierarchical hash tree based on each of the sub-data and the corresponding verification tag includes:

[0115] First, the verification label of each sub-data is used as the hash value of the leaf node, and the first root hash value is generated by calculating the hash value of the parent node layer by layer.

[0116] In one embodiment, a hierarchical hash tree is constructed using the verification tag of each sub-data as the hash value of the leaf nodes. The hash value of each leaf node also includes the shard ID and shard sequence number of the sub-data, preventing malicious replacement or reordering of nodes. The hash algorithm used to calculate the hash value of the parent node is determined by the number of leaf nodes in the current layer. For example, when the number of leaf nodes is ≤16, the SM3 algorithm is used (for national cryptographic compliance); when the number of leaf nodes is >16, the SHA-3 algorithm is used (for quantum resistance). The hash value of the parent node is generated by concatenating the bitwise XOR hash values ​​of the leaf nodes and then hashing them again. When the number of sub-data is not a power of 2, virtual leaf nodes (with all hash values ​​being 0) are used to ensure the balance of the hierarchical hash tree and avoid attack risks caused by differences in path length. The hierarchical hash tree is constructed in two ways: first, by grouping by shard ID to generate intermediate root hash values; second, by grouping by data type (such as text or image) to generate type root hash values. By calculating the hash value of the parent node layer by layer, the root hash value is finally generated. The root hash value contains the hash values ​​of all subtrees, and the quantum key hash value is embedded in the root hash value to ensure the strong correlation between the hierarchical hash tree and key updates.

[0117] Second, the first hash value is compared with the second hash value generated by the sending end to obtain the integrity verification result.

[0118] In one embodiment, the sending end uses a node reputation evaluation mechanism to prioritize storing intermediate layer hash values ​​of the hierarchical hash tree from nodes with high reputation (e.g., reputation value ≥ 0.8), thereby reducing the risk of data tampering. Specifically, when dynamically adjusting the routing path, the receiving end only needs to verify the intermediate layer hash value stored in the new routing path, without needing to recalculate the root hash value.

[0119] In one embodiment, the sender appends an SM9 signature to the hash path of each leaf node, and the receiver verifies both the signature and the root hash value during verification.

[0120] Step S204: When the integrity verification meets the preset conditions, the target data is reconstructed.

[0121] The embodiments of the present invention, by receiving and decrypting encrypted ciphertext, and performing integrity verification and reorganization based on verification tags and hierarchical hash trees, can ensure the consistency and integrity of all sub-data in distributed transmission and achieve reliable data recovery.

[0122] Optionally, in this embodiment of the invention, the step of performing integrity verification using a hierarchical hash tree based on each of the sub-data and the corresponding verification tag includes:

[0123] The verification label of each sub-data is used as the hash value of the leaf node. The first root hash value is generated by calculating the hash value of the parent node layer by layer.

[0124] The first hash value is compared with the second hash value generated by the sending end to obtain the integrity verification result.

[0125] The embodiments of the present invention can efficiently and accurately verify data integrity by comparing the first hash value generated by the receiving end with the second hash value provided by the sending end.

[0126] like Figure 3 As shown, based on the above-described method embodiments, another embodiment of a distributed data transmission method is provided, including steps S1 to S5:

[0127] Step S1 involves dividing the original data into multiple sub-data packets according to a dynamic fragmentation strategy. The dynamic fragmentation strategy dynamically adjusts the fragment size based on real-time network bandwidth, transmission delay, node load, and data type. Executing step S1 is equivalent to executing step S101.

[0128] Step S2: For each of the sub-data packets, a quantum key negotiation algorithm and a dynamic hybrid hash algorithm are used to generate encrypted ciphertext and a verification tag; wherein, executing step S2 is equivalent to executing steps S102 and S103.

[0129] Step S3 involves transmitting the sub-data packets in parallel through a distributed node network. The node network employs a blockchain-based node reputation evaluation mechanism, prioritizing high-reputation nodes as transmission paths. Executing step S3 is equivalent to executing step S104.

[0130] Step S4: The receiving end performs integrity verification on the sub-data packet according to the verification tag, and reassembles the original data after verifying data consistency using a hierarchical hash tree; wherein, executing step S4 is equivalent to executing steps S203 and S204.

[0131] Step S5: During data transmission, dynamically adjust the routing path based on real-time transmission quality feedback; wherein, executing step S5 is equivalent to the action of dynamically adjusting the routing path based on the weight function using the improved Dijkstra routing algorithm after executing step S104.

[0132] The embodiments of this invention improve fragmentation efficiency through the design of a dynamic fragmentation strategy; enhance key security by employing quantum key negotiation and hybrid hash algorithm encryption to resist quantum computing attacks and tampering; improve routing reliability during transmission through a blockchain-based node reputation evaluation mechanism; reduce end-to-end transmission latency through secure routing optimization design; and ensure consistency of all sub-data packets in distributed transmission through integrity verification and reassembly processes after transmission is completed.

[0133] Preferably, the distributed data transmission method provided in any of the above-described method embodiments of the present invention supports heterogeneous network environments; wherein, the heterogeneous network environment includes 5G, Wi-Fi 6 and satellite communication networks, and cross-platform compatibility is achieved through a protocol adaptation layer.

[0134] In one embodiment, the protocol adaptation layer is configured with a dynamic protocol adaptation mechanism, which specifically includes: real-time evaluation of network environment parameters through a multi-protocol adaptive engine; wherein the network environment parameters include bandwidth B, latency D, interference index I, network stability index SN (0-1), and encryption strength coefficient ES (0-1). Protocol adaptation weight W p The calculation formula is as follows:

[0135]

[0136] Where μ is the stability sensitivity coefficient, with 0.2 ≤ μ ≤ 0.5; SNR is the signal-to-noise ratio. According to W... p Choose the optimal transport protocol (such as MQTT, CoAP, or HTTP / 3) and implement cross-protocol data encapsulation through a protocol conversion layer.

[0137] This embodiment addresses the issues of single-mode protocol selection, low security, and static configuration by performing multi-dimensional dynamic weight calculations, joint optimization of protocols and routes, and deep binding of encryption strength and node reputation. By combining route weight-driven protocol switching with reputation-enhanced encryption strength, it maximizes service success rate, minimizes latency, and controls security risks, providing a highly adaptable and reliable dynamic protocol adaptation solution for heterogeneous network environments.

[0138] In one embodiment, the protocol conversion layer employs a deep learning-based protocol mapping model, including: establishing a protocol difference matrix KM and quantifying the semantic differences D between different protocols. s Grammatical differences D g Version differences D v Specifically, the semantic differences between protocols are analyzed using the BERT language model, syntactic differences are determined by comparing protocol syntax structures (such as field order and data format), and version differences are dynamically calculated based on the protocol version compatibility matrix. The protocol conversion efficiency E is calculated as follows:

[0139]

[0140] Among them, θ, φ and φ are difference weighting coefficients, satisfying e -(·) The exponential decay characteristic of E strictly limits the range of E to (0,1), avoiding the risk of overflow. This is achieved by dynamically adjusting θ... And φ, so that E≥95%. The difference weight coefficients can be dynamically allocated according to real-time network requirements. For example, in high-security scenarios, θ can be set to 0.6 (semantic differences prioritized to prevent semantic tampering); in low-latency scenarios, φ can be set to 0.6 (syntactic differences prioritized for fast field mapping); and in version-compatible scenarios... It can be set to 0.6 (prioritizing version differences to ensure protocol upgrade compatibility). When dynamically adjusting,

[0141] This embodiment solves the problems of inefficiency, manual dependence, and single-dimensional evaluation in protocol conversion by performing deep learning-driven 3D difference modeling, dynamic weight reinforcement learning optimization, and closed-loop linkage with multiple modules. By combining the parameter feedback of the adaptive engine and the dynamic adjustment of routing weights, it can maximize the efficiency of protocol conversion, minimize security risks, and improve end-to-end transmission reliability, providing intelligent and adaptive deep mapping technical support for heterogeneous protocol environments.

[0142] like Figure 4 As shown, based on the above method embodiments, an embodiment of a sending end is provided, including: a dynamic fragmentation module 401, a quantum encryption module 402, a hash verification module 403, and a data transmission module 404;

[0143] The dynamic sharding module 401 is used to dynamically shard the target data to obtain multiple sub-data; wherein, the shard size of the sub-data is adjusted according to the data type, real-time network bandwidth, transmission delay, node load rate and signal-to-noise ratio;

[0144] The quantum encryption module 402 is used to encrypt each of the sub-data based on a preset public key and private key using a quantum encryption function to obtain multiple encrypted ciphertexts; wherein, the private key is dynamically updated based on a quantum random number generator and a timestamp, and the public key is used for signature verification based on the Chinese national cryptographic SM9 algorithm;

[0145] The hash verification module 403 is used to perform mixed calculations on the SHA-3 hash value, SM3 hash value and SM9 hash value of each sub-data based on dynamic hash weights, to obtain multiple verification tags; wherein, the dynamic hash weights are allocated according to the data security level;

[0146] The data transmission module 404 is used to transmit each encrypted ciphertext and its corresponding verification tag to the receiving end in parallel through a distributed node network, so that the receiving end can decrypt each encrypted ciphertext to obtain each sub-data, and perform integrity verification using a hierarchical hash tree based on each sub-data and its corresponding verification tag. When the integrity verification meets a preset condition, the target data is reassembled. The transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism.

[0147] Optionally, in this embodiment of the invention, the dynamic sharding module 401 includes: a basic sharding submodule, a sharding coefficient submodule, and a dynamic sharding submodule;

[0148] The basic sharding submodule is used to set the basic sharding size according to the data type of the target data;

[0149] The fragmentation coefficient submodule is used to calculate dynamic fragmentation coefficients based on real-time network bandwidth, transmission delay, node load rate, and signal-to-noise ratio.

[0150] The dynamic sharding submodule is used to take the product of the basic sharding size and the dynamic sharding coefficient as the sharding size, and to dynamically shard the target data according to the sharding size to obtain multiple sub-data.

[0151] The embodiments of the present invention calculate dynamic fragmentation coefficients based on network bandwidth, latency, load, and signal-to-noise ratio, and determine the final fragmentation size, which enables data fragmentation to adapt to network fluctuations and improves transmission efficiency and stability.

[0152] Optionally, in this embodiment of the invention, the data transmission module 404 includes: a reputation value calculation submodule and a node filtering submodule;

[0153] The reputation value calculation submodule is used to calculate the reputation value of each node based on the node's transmission success rate, response time, resource utilization rate and protocol compatibility score within a preset time.

[0154] The node filtering submodule is used to select nodes with a reputation value greater than or equal to a preset reputation threshold as transmission nodes of the distributed node network.

[0155] This invention calculates a reputation value based on node transmission success rate, response time, resource utilization, and protocol compatibility, and then filters high-reputation nodes, which can effectively eliminate unreliable nodes and improve the reliability of the transmission path.

[0156] Optionally, in this embodiment of the invention, a path adjustment submodule is further included after the data transmission module 404;

[0157] The path adjustment submodule is used to monitor transmission quality in real time. When the transmission quality does not meet the preset conditions, the improved Dijkstra routing algorithm is used to dynamically adjust the routing path based on a weight function. The weight function is constructed based on real-time network bandwidth, transmission delay, and reputation value. The weight coefficient corresponding to the reputation value is constructed based on the real-time network congestion level.

[0158] This invention, through real-time monitoring of transmission quality and dynamic route adjustment using an improved Dijkstra algorithm, can optimize the path based on network congestion, latency, and node reputation, thereby reducing end-to-end transmission latency.

[0159] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement a distributed data transmission method provided by any of the above-described method embodiments of the present invention.

[0160] This invention, through its dynamic sharding module 401, dynamically adjusts the shard size based on data type and real-time network status, providing a data foundation for subsequent efficient distributed data transmission. The quantum encryption module 402 employs dynamically updated quantum keys and performs SM9 signature verification, effectively resisting quantum computing attacks and ensuring the trustworthiness of the key source. The hash verification module 403 dynamically mixes multiple hash values ​​to generate verification tags based on security levels, enhancing the strength of subsequent data integrity verification. The data transmission module 404 uses a blockchain-based reputation assessment mechanism to select high-reputation nodes for parallel transmission, improving the reliability of routing paths and reducing the risk of transmission failure.

[0161] like Figure 5 As shown, based on the above method embodiments, an embodiment of a receiving end is provided, including: a data receiving module 501, a data decryption module 502, a data verification module 503, and a data reassembly module 504;

[0162] The data receiving module 501 is used to receive each encrypted ciphertext and corresponding verification tag transmitted in parallel by the sending end through a distributed node network; wherein, the encrypted ciphertext is obtained by the sending end encrypting each sub-data using a quantum encryption function based on a preset public key and private key; the verification tag is obtained by the sending end performing mixed calculations on the SHA-3 hash value, SM3 hash value, and SM9 hash value of each sub-data based on dynamic hash weights; the sub-data is obtained by the sending end dynamically fragmenting the target data;

[0163] The data decryption module 502 is used to decrypt each of the encrypted ciphertexts to obtain each of the sub-data.

[0164] The data verification module 503 is used to perform integrity verification using a hierarchical hash tree based on each of the sub-data and the corresponding verification label;

[0165] The data reconstruction module 504 is used to reconstruct the target data when the integrity verification meets the preset conditions.

[0166] Optionally, in this embodiment of the invention, the data verification module 503 includes: a hash value calculation submodule and a hash value comparison submodule;

[0167] The hash value calculation submodule is used to take the verification label of each of the sub-data as the hash value of the leaf node, and generate the first root hash value by calculating the hash value of the parent node layer by layer.

[0168] The hash value comparison submodule is used to compare the first hash value with the second hash value generated by the sending end to obtain the integrity verification result.

[0169] The embodiments of the present invention can efficiently and accurately verify data integrity by comparing the first hash value generated by the receiving end with the second hash value provided by the sending end.

[0170] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement a distributed data transmission method provided by any of the above-described method embodiments of the present invention.

[0171] The embodiments of the present invention, by receiving and decrypting encrypted ciphertext, and performing integrity verification and reorganization based on verification tags and hierarchical hash trees, can ensure the consistency and integrity of all sub-data in distributed transmission and achieve reliable data recovery.

[0172] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0173] Based on the above-described embodiment of a distributed data transmission method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a distributed data transmission method according to any embodiment of the present invention.

[0174] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0175] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0176] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0177] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute a distributed data transmission method as described in any of the above-described method embodiments of the present invention.

[0178] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0179] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A distributed data transmission method, characterized in that, Applicable to the sending end, the distributed data transmission method includes: The target data is dynamically fragmented to obtain multiple sub-data; wherein, the fragment size of the sub-data is adjusted according to the data type, real-time network bandwidth, transmission delay, node load rate and signal-to-noise ratio. Based on a preset public key and private key, each of the sub-data is encrypted using a quantum encryption function to obtain multiple encrypted ciphertexts; wherein, the private key is dynamically updated based on a quantum random number generator and a timestamp, and the public key is used for signature verification based on the Chinese national cryptographic SM9 algorithm; Based on dynamic hash weights, the SHA-3 hash value, SM3 hash value, and SM9 hash value of each sub-data are mixed and calculated to obtain multiple verification tags; wherein, the dynamic hash weights are allocated according to the data security level; Each encrypted ciphertext and its corresponding verification tag are transmitted in parallel to the receiving end through a distributed node network, so that the receiving end can decrypt each encrypted ciphertext to obtain each sub-data. Based on each sub-data and its corresponding verification tag, a hierarchical hash tree is used to perform integrity verification. When the integrity verification meets the preset conditions, the target data is reassembled. The transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism.

2. The distributed data transmission method as described in claim 1, characterized in that, The target data is dynamically segmented to obtain multiple sub-data, including: Set the base fragment size according to the data type of the target data; The dynamic fragmentation coefficient is calculated based on real-time network bandwidth, transmission delay, node load rate, and signal-to-noise ratio. The product of the base partition size and the dynamic partition coefficient is used as the partition size, and the target data is dynamically partitioned according to the partition size to obtain multiple sub-data.

3. The distributed data transmission method as described in claim 1, characterized in that, The transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism, including: The reputation score of each node is calculated based on its transmission success rate, response time, resource utilization, and protocol compatibility score within a preset time. Nodes with a reputation value greater than or equal to a preset reputation threshold are designated as transmission nodes in the distributed node network.

4. The distributed data transmission method as described in claim 1, characterized in that, After transmitting each encrypted ciphertext and corresponding verification tag to the receiving end in parallel via a distributed node network, the method further includes: The transmission quality is monitored in real time. When the transmission quality does not meet the preset conditions, the improved Dijkstra routing algorithm is used to dynamically adjust the routing path based on the weight function. The weight function is constructed based on the real-time network bandwidth, transmission delay and reputation value. The weight coefficient corresponding to the reputation value is constructed based on the real-time network congestion level.

5. A distributed data transmission method, characterized in that, Applicable to the receiving end, the distributed data transmission method includes: The system receives encrypted ciphertexts and corresponding verification tags transmitted in parallel by the sending end through a distributed node network. The encrypted ciphertexts are obtained by the sending end encrypting each sub-data item using a quantum encryption function based on a preset public and private key. The verification tags are obtained by the sending end performing a mixed calculation on the SHA-3, SM3, and SM9 hash values ​​of each sub-data item based on dynamic hash weights. The sub-data items are obtained by the sending end dynamically fragmenting the target data. Decrypt each of the encrypted ciphertexts to obtain the corresponding sub-data; Based on each sub-data and its corresponding verification label, a hierarchical hash tree is used for integrity verification. When the integrity check meets the preset conditions, the target data is reconstructed.

6. A distributed data transmission method as described in claim 5, characterized in that, The step of performing integrity verification using a hierarchical hash tree based on each of the sub-data and the corresponding verification label includes: The verification label of each sub-data is used as the hash value of the leaf node. The first root hash value is generated by calculating the hash value of the parent node layer by layer. The first hash value is compared with the second hash value generated by the sending end to obtain the integrity verification result.

7. A transmitter, characterized in that, include: Dynamic sharding module, quantum encryption module, hash verification module, and data transmission module; The dynamic sharding module is used to dynamically shard the target data to obtain multiple sub-data; wherein, the shard size of the sub-data is adjusted according to the data type, real-time network bandwidth, transmission delay, node load rate and signal-to-noise ratio; The quantum encryption module is used to encrypt each of the sub-data based on a preset public key and private key using a quantum encryption function, thereby obtaining multiple encrypted ciphertexts; wherein, the private key is dynamically updated based on a quantum random number generator and a timestamp, and the public key is used for signature verification based on the Chinese national cryptographic algorithm SM9; The hash verification module is used to perform mixed calculations on the SHA-3 hash value, SM3 hash value and SM9 hash value of each sub-data based on dynamic hash weights, to obtain multiple verification tags; wherein, the dynamic hash weights are allocated according to the data security level; The data transmission module is used to transmit each encrypted ciphertext and its corresponding verification tag to the receiving end in parallel through a distributed node network, so that the receiving end can decrypt each encrypted ciphertext to obtain each sub-data, and perform integrity verification using a hierarchical hash tree based on each sub-data and its corresponding verification tag. When the integrity verification meets a preset condition, the target data is reassembled. The transmission nodes of the distributed node network are screened using a blockchain-based node reputation evaluation mechanism.

8. A receiving end, characterized in that, include: The system includes a data receiving module, a data decryption module, a data verification module, and a data reconstruction module. The data receiving module is used to receive each encrypted ciphertext and corresponding verification tag transmitted in parallel by the sending end through a distributed node network; wherein, the encrypted ciphertext is obtained by the sending end encrypting each sub-data using a quantum encryption function based on a preset public key and private key; the verification tag is obtained by the sending end performing mixed calculations on the SHA-3 hash value, SM3 hash value, and SM9 hash value of each sub-data based on dynamic hash weights; the sub-data is obtained by the sending end dynamically fragmenting the target data; The data decryption module is used to decrypt each of the encrypted ciphertexts to obtain each of the sub-data. The data verification module is used to perform integrity verification using a hierarchical hash tree based on each of the sub-data and the corresponding verification label. The data reconstruction module is used to reconstruct the target data when the integrity verification meets the preset conditions.

9. A terminal device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements a distributed data transmission method as described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform a distributed data transmission method as described in any one of claims 1-6.

Images