Novel data transmission interaction mode

Abstract

The invention discloses a novel data transmission interaction mode, which belongs to the technical field of data transmission interaction, and comprises the following steps of: performing dual authentication through quantum key distribution and biological characteristics, monitoring and analyzing a network state in real time through AI after the dual authentication, dynamically selecting an optimal transmission path and distributing a load. By combining dynamic weight adjustment and path priority scoring, path optimization which is more intelligent than that of a traditional dynamic routing protocol is realized, an optimal path can be more accurately selected through comprehensive scoring and correlation interference resistance coefficients, and a dynamic load distribution formula ensures flow balance, maximizes the network utilization rate, reduces congestion and delay and improves the routing efficiency. The path correlation suppression mechanism can avoid multi-path simultaneous congestion, improves the overall reliability of the system, and is suitable for a complex network environment.

Description

Technical Field

[0001] The present invention belongs to the technical field of data transmission and interaction, and specifically refers to a new type of data transmission and interaction method. Background Art

[0002] In the field of data transmission, traditional technologies have significant limitations in terms of security, transmission efficiency, dynamic adaptability, and data integrity. There is a need for a new type of interaction method that is more efficient, more secure, and more flexible.

[0003] However, there are still certain defects in existing data transmission and interaction. Existing data transmission and interaction rely on fixed measurement criteria to select paths, unable to analyze multi-dimensional network status in real time, unable to quickly respond to network dynamic changes, resulting in sub-optimal path selection, leading to congestion or high latency. Static weight allocation easily causes uneven traffic distribution, with some paths overloaded while others are idle, resulting in low network utilization. Multiple paths may be congested simultaneously due to state correlation, and there is a lack of a method to suppress the priority of redundant paths. Traditional fragmentation techniques usually use fixed fragmentation sizes and cannot dynamically adjust according to channel quality, with limited error correction capabilities. Traditional transmission parameters are usually statically configured and not optimized in combination with service types and real-time network status. Transmission lacks end-to-end security protection and automated fault tolerance capabilities, relying on centralized logging and manual intervention. Therefore, a new type of data transmission and interaction method is proposed. Summary of the Invention

[0004] The purpose of the present invention is to provide a new type of data transmission and interaction method to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A new type of data transmission and interaction method, including the following steps:

[0006] S1. Perform dual authentication through quantum key distribution and biometric features;

[0007] S2. After dual authentication, use AI to monitor and analyze the network status in real time, dynamically select the optimal transmission path, and allocate the load;

[0008] S3. After selecting the transmission path, fragment the data and add error correction codes, and adaptively adjust the fragment size according to the channel quality;

[0009] S4. Bypass congested areas through cascaded paths and optimize the transmission direction according to the device location;

[0010] S5. After completing data preparation and transmission path planning, dynamically adjust the transmission parameters according to the service type, and pre-store high-frequency data through distributed caching;

[0011] S6. Record the transmission status through blockchain, automatically trigger FEC repair after detecting packet loss, and isolate abnormal channels;

[0012] S7. Dynamically close idle channels while periodically updating encryption keys and authentication information.

[0013] Among them, for the above-mentioned S1, it performs dual authentication through quantum key distribution and biometrics; builds a quantum key distribution system, including transmitter and receiver devices, initializes the quantum key distribution system, the transmitter generates a quantum state signal and sends it to the receiver, after the receiver receives the quantum state signal, it measures the signal, and the transmitter and receiver perform information comparison and error correction through a classical communication channel. After comparison and error correction, both parties finally generate and confirm the shared quantum key; collects user biometric data through sensors, preprocesses the original biometric data, including denoising, standardization, and feature extraction, converts the extracted biometric vectors into encrypted biometric templates, and stores them in a secure database. The user submits real-time biometrics, extracts features and compares them with the stored biometric templates. If the biometric verification is passed, the system binds the quantum key to the user identity and periodically triggers the update of the quantum key, and real-time monitors the bit error rate and transmission anomalies of the quantum channel. If the detected error rate exceeds the standard, an alarm is triggered and the key distribution is terminated.

[0014] Among them, for the above-mentioned S2, after dual authentication, it uses AI to monitor and analyze the network status in real time, dynamically selects the optimal transmission path and allocates the load; after dual authentication, it uses the Telemetry protocol of network devices to collect multi-dimensional network metrics in real time, including bandwidth utilization B t 、latency D t 、packet loss rate L t and device load C t , and comprehensively scores the network status according to the multi-dimensional network metrics collected in real time. The implementation formula is:

[0015]

[0016] In the formula, S t represents the comprehensive network status score at time t, B t represents the current bandwidth utilization, B max represents the maximum broadband capacity of the path, D t represents the current latency, D thres represents the preset latency threshold, L t represents the current packet loss rate, C t represents the device load, C cap represents the upper limit of the device load, and α, β, γ, δ represent dynamically adjustable weights;

[0017] According to the status score S t,i of path i, historical stability Stb i and service priority bpi Perform path priority scoring, and the implementation formula is:

[0018]

[0019] In the formula, P t,i represents the priority score of path i at time t, S t,i represents the status score of path i, Stb i represents the historical stability of path i, bp i represents the service priority of path i, ∈ represents the anti-correlation interference coefficient, Corr(S t,i , S t,j ) represents the status correlation between path i and j.

[0020] Among them, the S2, according to the path priority P t,i , the total traffic Q t and the path capacity Q cap,i perform dynamic load distribution ratio, and the implementation formula is:

[0021]

[0022] In the formula, λ t,i represents the load ratio allocated to path i at time t, P t,i represents the priority score of path i at time t, η represents the temperature coefficient, Q t represents the current total traffic demand, Q cap,i represents the maximum carrying capacity of path i, min represents the constraint that the line does not exceed the physical capacity, represents ensuring that the load does not exceed the path capacity Q cap,i .

[0023] By analyzing the network status in real time through the AI algorithm, combined with dynamic weight adjustment and path priority scoring, a path optimization more intelligent than the traditional dynamic routing protocol is achieved. Through comprehensive scoring and anti-correlation interference coefficient, the optimal path can be selected more accurately. The dynamic load distribution formula ensures traffic balance, maximizes network utilization, reduces congestion and delay. The path correlation suppression mechanism can avoid simultaneous congestion of multiple paths and improve the overall reliability of the system, which is applicable to complex network environments.

[0024] Among them, the S3, after selecting the transmission path, fragment the data and add error correction codes, and adaptively adjust the fragment size according to the channel quality; divide the data into fragments, add error correction codes, and dynamically adjust the fragment size according to the real-time channel quality, initialize the fragment size according to the preset default fragment size and channel quality baseline, and obtain the real-time quality indicators of the current transmission path, including the bandwidth utilization rate B t , packet loss rate L t, the delay jitter J is calculated, and the channel quality score Qd is implemented as follows:

[0025]

[0026] Among them, the lower the value of Qd ∈ [0, 1], the worse the channel quality. According to the channel quality score Qd, the shard size is adjusted. According to the channel score, it is divided into low-quality channels, medium-quality channels, and high-quality channels. When the channel score is a low-quality channel, the shard is reduced. When the channel score is a medium-quality channel, the default shard is maintained. When the channel score is a high-quality channel, the shard is increased.

[0027] Among them, in S3, the original data is divided into N shards according to the shard size S. An error correction code scheme is selected for each shard, and metadata is added to each encoded shard. The encapsulated shards and the error correction code are combined into a transmission unit. The shards are distributed to the target nodes according to the path planning S2, and the transmission success rate is recorded at the same time. If a shard transmission failure is detected, error correction code repair is triggered. The error bit is located and repaired through the error correction code bits. The shard strategy is dynamically adjusted according to the repair result.

[0028] Among them, in S4, the congestion area is bypassed through the cascaded path, and the transmission direction is optimized according to the device location; the prepared data is obtained, and according to the load ratio λ of S2 t,i , the shards are proportionally allocated to each path. The shards with high error correction requirements are preferentially allocated to the high-reliability paths. If a certain path is congested, cascaded path switching is triggered, and the shards are re-routed to the alternate paths. The transmission status of the shards is tracked in real time, and the paths and shard indexes of the failed shards are recorded. If the single-path transmission failure rate exceeds the threshold, S2 is triggered to recalculate the path priority and adjust the load distribution. The receiving end automatically repairs the damaged shards according to the indexes and error correction codes in the metadata. If the repair fails, S3 is triggered to re-transmit the shard. The transmission success rate, delay, and packet loss rate indicators are fed back to S2 to dynamically adjust the weight coefficients. If a high path correlation is detected, the redundant path priority is reduced through the path correlation suppression mechanism of S4.

[0029] Among them, in S5, after the data preparation and transmission path planning are completed, the transmission parameters are dynamically adjusted according to the service type, and the high-frequency data is pre-stored through distributed caching; the service type is defined according to the current task, and the parameter templates of different service types are predefined. The bandwidth, delay, and packet loss rate of the current path are obtained through the AI monitoring of S2 for parameter dynamic adjustment. By analyzing the historical access logs, the high-frequency data shards are hashed by consistent hashing and allocated to the distributed cache nodes.

[0030] Among them, in S6, the transmission status is recorded through the blockchain. After detecting packet loss, FEC repair is automatically triggered, and abnormal channels are isolated; a blockchain transaction is generated for each transmitted data packet, including the data packet hash, sending timestamp, target address, transmission path, and FEC redundancy information. The hash of the FEC redundant data is extracted from the blockchain transaction, the redundant data block is obtained from the distributed cache, the original data block and the redundant data block are XOR-operated to recover the lost shard, a repaired data packet is generated and recorded on the chain again, a channel isolation transaction is generated, including the channel ID and isolation timestamp, which is uploaded to the chain and broadcast to notify S2 of path selection, the abnormal channel is removed from the available path list, triggering S4 cascaded path switching, selecting an alternative path to transmit subsequent data, and regularly re-detecting the channel status.

[0031] Dynamically closing idle channels can release resources, reduce the potential attack surface, and enhance system security. Regularly updating encryption keys and authentication information prevents the risk of long-term key leakage or cracking, avoids the vulnerability of using the same key multiple times in traditional static keys, and forms a closed loop with the quantum key distribution of S1, ensuring the continuous security of keys and the adaptive protection ability of the system. Compared with the static key strategy, the dynamic key update mechanism significantly extends the cracking time window of attackers and is applicable to scenarios with long-term high-security requirements.

[0032] Compared with the prior art, the beneficial effects of the present invention are:

[0033] 1. Through real-time analysis of the network status by the AI algorithm of the present invention, combined with dynamic weight adjustment and path priority scoring, more intelligent path optimization than traditional dynamic routing protocols is achieved. Through comprehensive scoring and anti-correlation interference coefficients, the optimal path can be selected more accurately. The dynamic load distribution formula ensures traffic balance, maximizes network utilization, reduces congestion and latency, and the path correlation suppression mechanism can avoid simultaneous congestion of multiple paths, enhancing the overall reliability of the system and being applicable to complex network environments;

[0034] 2. The robustness of data transmission is significantly improved by the present invention through the sharding technology combined with the adaptive error correction code. By dynamically adjusting the shard size based on real-time evaluation of channel quality, compared with the fixed shard size, the number of retransmissions is reduced, and the bandwidth utilization is optimized. The error correction code further reduces the dependence on high-reliability hardware, and even if some shards are lost, they can be recovered through redundant data, especially applicable to unreliable network environments. The intelligent allocation of shards and paths further improves the overall transmission success rate;

[0035] 3. By dynamically adjusting parameters according to the service type, the present invention significantly improves resource utilization. The distributed cache pre-stores high-frequency data, reducing the need for repeated transmissions, consuming less bandwidth, reducing resource waste, and achieving precise pre-storage of hot data through historical access log analysis, especially applicable to cloud storage or CDN scenarios;

[0036] 4. The present invention ensures the transparency and credibility of the transmission status record through the immutability of the blockchain. The hash, path, and timestamp information of each shard are permanently recorded, avoiding the single-point failure or tampering risk of the centralized log. The FEC automatic repair reduces manual intervention and improves the data recovery efficiency. When packet loss or verification failure is detected, repair can be immediately triggered and the result recorded to ensure data integrity. The blockchain isolation transaction broadcast mechanism for abnormal channels enables the entire network nodes to synchronously update the path selection strategy, avoiding the spread of abnormal paths and affecting other transmission tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is the operation flow of a new data transmission and interaction method of the present invention Figure 1 ;

[0038] Figure 2 is the operation flow of a new data transmission and interaction method of the present invention Figure 2 ;

[0039] Figure 3 is the operation flow of a new data transmission and interaction method of the present invention Figure 3 ;

[0040] Figure 4 is the operation flow of a new data transmission and interaction method of the present invention Figure 4 。 DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0042] Embodiment

[0043] Please refer to Figures 1-4 shown in the figure, the present invention provides a technical solution, including the following steps:

[0044] S1. Perform dual authentication through quantum key distribution and biometric features;

[0045] S2. After dual authentication, dynamically select the optimal transmission path and allocate the load by real-time monitoring and analyzing the network status through AI;

[0046] S3. After selecting the transmission path, fragment the data and add error correction codes, and adaptively adjust the fragment size according to the channel quality;

[0047] S4. Bypass the congested area through a cascading path and optimize the transmission direction according to the device location;

[0048] S5. After completing data preparation and transmission path planning, dynamically adjust transmission parameters according to the service type, and pre-store high-frequency data through distributed caching;

[0049] S6. Record the transmission status through blockchain, automatically trigger FEC repair after detecting packet loss, and isolate abnormal channels;

[0050] S7. Dynamically close idle channels, and at the same time periodically update encryption keys and authentication information.

[0051] Among them, for the said S1, perform dual authentication through quantum key distribution and biometrics; build a quantum key distribution system, including transmitter and receiver devices, perform initialization settings on the quantum key distribution system, the transmitter generates quantum state signals and sends them to the receiver, after the receiver receives the quantum state signals, it measures them, and the transmitter and receiver perform information comparison and error correction through a classical communication channel. After comparison and error correction, both parties finally generate and confirm the shared quantum key; collect user biometric data through sensors, preprocess the original biometric data, including denoising, standardization and feature extraction, convert the extracted biometric vectors into encrypted biometric templates, and store them in a secure database. The user submits real-time biometrics, extracts features and compares them with the stored biometric templates. If the biometric verification passes, the system binds the quantum key to the user identity and periodically triggers the update of the quantum key, and real-time monitors the bit error rate and transmission anomalies of the quantum channel. If it detects that the error rate exceeds the standard, it triggers an alarm and terminates the key distribution.

[0052] Among them, for the said S2, after dual authentication, use AI to monitor and analyze the network status in real time, dynamically select the optimal transmission path and allocate loads; after dual authentication, use the Telemetry protocol of network devices to collect multi-dimensional network metrics in real time, including bandwidth utilization B t , latency D t , packet loss rate L t and device load C t , perform a comprehensive network status score based on the multi-dimensional network metrics collected in real time. The implementation formula is:

[0053]

[0054] In the formula, S t represents the comprehensive network status score at time t, B t represents the current bandwidth utilization, B max represents the maximum broadband capacity of the path, D t represents the current latency, D thres represents the preset latency threshold, Lt Represents the current packet loss rate, C t Represents the device load, C cap Represents the upper limit of device load, and α, β, γ, δ represent dynamic adjustment weights;

[0055] According to the status score S of path i t,i , historical stability Stb i and service priority bp i Perform path priority scoring, and the implementation formula is:

[0056]

[0057] In the formula, P t,i Represents the priority score of path i at time t, S t,i Represents the status score of path i, Stb i Represents the historical stability of path i, bp i Represents the service priority of path i, ∈ represents the anti-correlation interference coefficient, Corr(S t,i ,S t,j ) Represents the status correlation between path i and j.

[0058] Among them, the S2, according to the path priority P t,i , total traffic Q t and path capacity Q cap,i Perform dynamic load distribution ratio, and the implementation formula is:

[0059]

[0060] In the formula, λ t,i Represents the load ratio allocated to path i at time t, P t,i Represents the priority score of path i at time t, η represents the temperature coefficient, Q t Represents the current total traffic demand, Q cap,i Represents the maximum carrying capacity of path i, min represents the constraint that the line does not exceed the physical capacity, Represents ensuring that the load does not exceed the path capacity Q cap,i .

[0061] By analyzing the network status in real time through the AI algorithm, combined with dynamic weight adjustment and path priority scoring, it realizes a more intelligent path optimization than traditional dynamic routing protocols. Through comprehensive scoring and anti-correlation interference coefficient, it can more accurately select the optimal path. The dynamic load distribution formula ensures traffic balance, maximizes network utilization, reduces congestion and latency. The path correlation suppression mechanism can avoid simultaneous congestion of multiple paths and improve the overall reliability of the system, and is applicable to complex network environments.

[0062] Among them, in step S3, after selecting the transmission path, the data is fragmented and error correction codes are added, and the fragment size is adaptively adjusted according to the channel quality; the data is divided into fragments, error correction codes are added, and the fragment size is dynamically adjusted according to the real-time channel quality. The fragment size is initialized according to the preset default fragment size and the channel quality baseline, and the real-time quality metrics of the current transmission path are obtained, including the bandwidth utilization rate B t , packet loss rate L t , and delay jitter J. The channel quality score Qd is calculated and implemented as:

[0063]

[0064] Among them, the lower the value of Qd ∈ [0, 1], the worse the channel quality. According to the channel quality score Qd, the fragment size is adjusted. According to the channel score, it is divided into low-quality channels, medium-quality channels, and high-quality channels. When the channel score is a low-quality channel, the fragment is reduced; when the channel score is a medium-quality channel, the default fragment is maintained; when the channel score is a high-quality channel, the fragment is increased.

[0065] Among them, in step S3, the original data is divided into N fragments according to the fragment size S, an error correction code scheme is selected for each fragment, and metadata is added to each encoded fragment. The encapsulated fragment and the error correction code are combined into a transmission unit, and the fragments are distributed to the target nodes according to the path planning S2. At the same time, the transmission success rate is recorded. If a fragment transmission failure is detected, error correction code repair is triggered, the error bit is located and repaired through the error correction code bits, and the fragment strategy is dynamically adjusted according to the repair result.

[0066] Among them, in step S4, the congestion area is bypassed through the cascaded path, and the transmission direction is optimized according to the device location; the prepared data is obtained, and according to the load ratio λ of S2 t,i , the fragments are proportionally allocated to each path. The fragments with high error correction requirements are preferentially allocated to the high-reliability paths. If a certain path is congested, cascaded path switching is triggered, and the fragments are re-routed to the backup paths. The transmission status of the fragments is tracked in real time, and the paths and fragment indexes of the failed fragments are recorded. If the single-path transmission failure rate exceeds the threshold, S2 is triggered to recalculate the path priority and adjust the load distribution. The receiving end automatically repairs the damaged fragments according to the indexes and error correction codes in the metadata. If the repair fails, S3 is triggered to re-transmit the fragment. The transmission success rate, delay, and packet loss rate metrics are fed back to S2 to dynamically adjust the weight coefficients. If high path correlation is detected, the redundant path priority is reduced through the path correlation suppression mechanism of S4.

[0067] Among them, for the said S5, after completing data preparation and transmission path planning, it dynamically adjusts transmission parameters according to the service type, and pre-stores high-frequency data through distributed caching; defines the service type according to the current task, pre-defines parameter templates for different service types, obtains the bandwidth, latency, and packet loss rate of the current path through the AI monitoring of S2, performs dynamic parameter adjustment, analyzes historical access logs, shards high-frequency data through consistent hashing, and distributes it to distributed cache nodes.

[0068] Among them, for the said S6, it records the transmission status through the blockchain, automatically triggers FEC repair after detecting packet loss, and isolates abnormal channels; generates a blockchain transaction for each transmitted data packet, including the data packet hash, send timestamp, target address, transmission path, and FEC redundancy information, extracts the hash of the FEC redundancy data from the blockchain transaction, obtains the redundant data block from the distributed cache, performs an exclusive OR operation on the original data block and the redundant data block to recover the lost shard, generates a repaired data packet and records it on the chain again, generates a channel isolation transaction, including the channel ID and isolation timestamp, uploads it to the chain and broadcasts it, notifies S2 of path selection, removes the abnormal channel from the available path list, triggers the S4 cascaded path switching, selects an alternative path to transmit subsequent data, and periodically re-detects the channel status.

[0069] Dynamically closing idle channels can release resources, reduce the potential attack surface, and enhance system security. Regularly updating encryption keys and authentication information prevents the risk of long-term key leakage or cracking, avoids the vulnerability of using the same key multiple times in traditional static keys, and forms a closed loop with the quantum key distribution of S1, ensuring the continuous security of the keys and the adaptive protection ability of the system. Compared with the static key strategy, the dynamic key update mechanism significantly extends the attacker's cracking time window and is applicable to scenarios with long-term high-security requirements.

[0070] Working principle: Generate a quantum state signal at the transmitter, send it to the receiver through the quantum channel, the receiver measures the quantum state, compares the measurement results with the transmitter through the classical communication channel, filters out the shared quantum key, and ensures the uniqueness and security of the key through error correction and privacy amplification technologies. The user submits biometric features, which are collected and preprocessed by the sensor, the feature vector is extracted and encrypted into a biometric template, and compared with the template in the security database to verify the identity. After successful verification, the quantum key is bound to the user identity, and the key is updated regularly to prevent leakage. Continuously monitor the bit error rate and transmission anomalies of the quantum channel. If an anomaly is detected, immediately trigger an alarm and terminate the key distribution;

[0071] Collect multi-dimensional metrics from network devices (such as routers and switches) through the Telemetry protocol: bandwidth utilization, latency, packet loss rate, device load, etc. The AI algorithm comprehensively scores and combines metrics such as bandwidth, latency, packet loss rate, and load to dynamically calculate the network status score. Prioritize selecting paths with high scores. Calculate the path priority score based on the historical stability, service priority, and anti-correlation interference coefficient of the path. Allocate the total traffic according to the path priority to ensure that the path capacity is not exceeded. Real-time feedback metrics such as transmission success rate and latency, dynamically adjust the weight coefficients, and optimize the path selection strategy. Dynamically adjust the shard size according to the channel quality, add error correction codes to each shard. The redundant data is used to repair transmission errors. The shards are transmitted through the path selected by S2. If a shard loss or check failure is detected, trigger the error correction code repair. The receiving end locates the error bit through the redundant data and repairs it. If the repair fails, re-transmit the shard. Dynamically adjust the shard strategy according to the repair result. If the main path is congested, trigger the cascaded path switch, route the shards to the alternate path. Prioritize allocating shards with high error correction requirements to highly reliable paths and low-priority shards to redundant paths. Optimize the transmission direction according to the device geographical location to reduce the relay hops and transmission distance. If the single-path failure rate exceeds the threshold, trigger S2 to recalculate the path priority, reduce the weight of this path, and isolate the abnormal channel through S6. Load the predefined parameter template according to the current task type, and adjust the parameters in real-time through the AI monitoring of S2. Analyze the historical access logs, identify high-frequency data, and shard and store the high-frequency data in the distributed cache nodes through consistent hashing. Generate a blockchain transaction for each data packet, recording the hash, timestamp, path, and FEC redundancy information. If a packet loss is detected, extract the redundant data hash from the blockchain transaction, obtain the redundant block through the distributed cache. The receiving end restores the lost shard through XOR operation, and the repaired data is re-recorded on the chain. If the channel packet loss rate continues to exceed the standard, generate a channel isolation transaction and broadcast it. All network nodes synchronously remove this channel, trigger S4 to switch to the alternate path, and periodically re-detect the channel status to restore availability. Dynamically close unused transmission channels to release bandwidth and computing resources. Regularly update the quantum key and biometric template, and ensure the secure distribution of the new key through the quantum key distribution mechanism of S1.

[0072] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

[0073] The above description of the present invention and its embodiments is not restrictive. What is shown in the drawings is only one of the embodiments of the present invention, and the actual structure is not limited thereto. In general, if those of ordinary skill in the art are inspired by it and, without departing from the spirit of the present invention, design similar structural forms and embodiments to this technical solution without creative efforts, they shall fall within the protection scope of the present invention.

Claims

1. A new data transmission and interaction method, characterized in that It includes the following steps: S1. Perform dual authentication through quantum key distribution and biometrics; S2. After dual authentication, dynamically select the optimal transmission path and allocate loads by means of real-time monitoring and analysis of the network status by AI; S3. After selecting the transmission path, fragment the data and add error correction codes, and adaptively adjust the fragment size according to the channel quality; S4. Bypass congested areas through cascaded paths and optimize the transmission direction according to the device location; S5. After completing data preparation and transmission path planning, dynamically adjust transmission parameters according to the service type, and pre-store high-frequency data through distributed caching; S6. Record the transmission status through blockchain, automatically trigger FEC repair after detecting packet loss, and isolate abnormal channels; S7. Dynamically close idle channels, and at the same time periodically update encryption keys and authentication information.

2. A novel data transmission and interaction method according to claim 1, characterized in that: In S1, perform dual authentication through quantum key distribution and biometrics; build a quantum key distribution system, including a transmitter and a receiver device, perform initialization settings on the quantum key distribution system, the transmitter generates a quantum state signal and sends it to the receiver, after the receiver receives the quantum state signal, it measures the signal, and the transmitter and the receiver perform information comparison and error correction through a classical communication channel. After comparison and error correction, both parties finally generate and confirm the shared quantum key; collect user biometric data through sensors, preprocess the original biometric data, including denoising, standardization and feature extraction, convert the extracted biometric vector into an encrypted biometric template, and store it in a secure database. The user submits real-time biometrics, extracts features and compares them with the stored biometric templates. If the biometric verification is passed, the system binds the quantum key to the user identity and periodically triggers the update of the quantum key, and real-time monitors the bit error rate and transmission anomalies of the quantum channel. If the detected error rate exceeds the standard, an alarm is triggered and the key distribution is terminated.

3. A novel data transmission and interaction method according to claim 1, characterized in that: S2, after dual authentication, the network status is monitored and analyzed in real time by AI, and the optimal transmission path is dynamically selected and the load is allocated; after dual authentication, multi-dimensional network metrics are collected in real time through the Telemetry protocol of network devices, including bandwidth utilization B t , latency D t , packet loss rate L t and device load C t . The comprehensive network status score is calculated based on the multi-dimensional network metrics collected in real time. The implementation formula is: In the formula, S t represents the comprehensive network state score at time t, B t represents the current bandwidth utilization rate, B max represents the maximum broadband capacity of the path, D t represents the current delay, D thres represents the preset delay threshold, L t represents the current packet loss rate, C t represents the device load, C cap represents the upper limit of the device load, and α, β, γ, δ represent the dynamic adjustment weights; Path priority score S based on the status of path i t,i , historical stability Stb i and business priority bp i Perform path priority scoring, and the implementation formula is: In the formula, P t,i represents the priority score of path i at time t, S t,i represents the state score of path i, Stb i represents the historical stability of path i, bp i represents the service priority of path i, ∈ represents the anti-correlation interference coefficient, Corr(S t,i ,S t,j ) represents the state correlation between path i and j.

4. A novel data transmission and interaction method according to claim 3, characterized in that: The said S2, according to the path priority P t,i , the total flow Q t and the path capacity Q cap,i to perform dynamic load distribution ratio, and the implementation formula is: In the formula, λ t,i represents the load ratio assigned to path i at time t, P t,i represents the priority score of path i at time t, η represents the temperature coefficient, Q t represents the current total traffic demand, Q cap,i represents the maximum carrying capacity of path i, and min represents the constraint that the line does not exceed the physical capacity.

5. A novel data transmission and interaction method according to claim 1, characterized in that: In step S3, after selecting a transmission path, the data is fragmented and error correction codes are added, and the fragment size is adaptively adjusted according to the channel quality; the data is segmented into fragments, error correction codes are added, and the fragment size is dynamically adjusted according to the real-time channel quality. The fragment size is initialized according to a preset default fragment size and a channel quality baseline, and real-time quality metrics of the current transmission path are obtained, including the bandwidth utilization rate B t , packet loss rate L t , and latency jitter J. The channel quality score Qd is calculated and implemented as follows: Among them, the lower the value of Qd ∈ [0,1], the worse the channel quality. According to the channel quality score Qd, adjust the fragment size. According to the channel score, it is divided into low-quality channels, medium-quality channels and high-quality channels. When the channel score is a low-quality channel, reduce the fragment size. When the channel score is a medium-quality channel, keep the default fragment size. When the channel score is a high-quality channel, increase the fragment size.

6. A novel data transmission and interaction method according to claim 5, characterized in that: In S3, divide the original data into N fragments according to the fragment size S, select an error correction code scheme for each fragment, and add metadata to each encoded fragment. Combine the encapsulated fragments and error correction codes into a transmission unit, distribute the fragments to the target nodes according to the path planning in S2, and at the same time record the transmission success rate. If a fragment transmission failure is detected, trigger error correction code repair, locate the error bit through the error correction code bit and repair it, and dynamically adjust the fragment strategy according to the repair result.

7. A novel data transmission and interaction method according to claim 1, characterized in that: In step S4, bypass the congested area through the cascaded path and optimize the transmission direction according to the device location; obtain the prepared data, and according to the load ratio λ in S2 t,i , allocate the shards to each path proportionally, preferentially allocate the shards with high error correction requirements to the highly reliable paths. If a certain path is congested, trigger the cascaded path switching, re-route the shards to the backup paths, track the shard transmission status in real time, record the paths and shard indexes of the failed shards. If the single-path transmission failure rate exceeds the threshold, trigger S2 to recalculate the path priorities and adjust the load distribution. The receiving end automatically repairs the damaged shards according to the indexes and error correction codes in the metadata. If the repair fails, trigger S3 to re-transmit the shard, feedback the transmission success rate, latency, and packet loss rate metrics to S2 to dynamically adjust the weight coefficients. If it is detected that the path correlation is high, reduce the priority of the redundant paths through the path correlation suppression mechanism in S4.

8. A novel data transmission and interaction method according to claim 1, characterized in that: In S5, after completing data preparation and transmission path planning, transmission parameters are dynamically adjusted according to the service type, and high-frequency data is pre-stored through distributed caching; the service type is defined according to the current task, parameter templates for different service types are predefined, the bandwidth, latency, and packet loss rate of the current path are obtained through AI monitoring in S2, parameter dynamic adjustment is performed, and by analyzing historical access logs, high-frequency data is sharded through consistent hashing and distributed to distributed cache nodes.

9. A novel data transmission and interaction method according to claim 1, characterized in that: In S6, the transmission status is recorded through the blockchain, FEC repair is automatically triggered after detecting packet loss, and abnormal channels are isolated; a blockchain transaction is generated for each transmitted data packet, including the data packet hash, send timestamp, target address, transmission path, and FEC redundancy information. The hash of the FEC redundant data is extracted from the blockchain transaction, the redundant data block is obtained from the distributed cache, the original data block and the redundant data block are XOR-operated to restore the lost shard, a repaired data packet is generated and recorded on the chain again, a channel isolation transaction is generated, including the channel ID and isolation timestamp, which is uploaded to the chain and broadcast to notify S2 of path selection, the abnormal channel is removed from the available path list, triggering S4 cascaded path switching, selecting an alternative path to transmit subsequent data, and regularly re-detecting the channel status.

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