Data quality analysis method in quantum communication data transmission process

Abstract

The invention relates to the technical field of data transmission, in particular to a data quality analysis method for a quantum communication data transmission process. The method comprises the following steps: acquiring a real-time key negotiation data set, analyzing the real-time key negotiation data set, and determining a real-time negotiation error rate; comparing the real-time negotiation bit error rate with a protocol bit error rate security threshold, and judging whether an interference-driven key toughness reconstruction mechanism needs to be activated or not according to a comparison result; and if the interference-driven key toughness reconstruction mechanism needs to be activated, trap filtering and key fragment multiplexing and splicing processing are performed on a plurality of survivor bits in the key negotiation process according to the interference-driven key toughness reconstruction mechanism, and a toughness reconstruction key is determined and output. According to the invention, the two communication parties can still efficiently negotiate to obtain the security key under the continuous high-intensity communication interference of the third party, the robustness and availability of the quantum key distribution service are improved, and the quantum communication quality is improved.

Description

Technical Field

[0001] This application relates to the field of data transmission technology, and in particular to a data quality analysis method for quantum communication data transmission processes. Background Technology

[0002] Quantum key distribution technology is a technique that uses the principles of quantum mechanics (uncertainty and no cloning) to securely distribute shared keys between communicating parties. Its core value lies in its ability to detect the behavior of attackers, and its security is based on physical laws rather than mathematical problems, providing secure keys for efficient data encryption during communication.

[0003] However, existing quantum key distribution technologies are prone to a sharp decline in key distribution efficiency or even interruption of key distribution communication when faced with high-intensity interference from attackers who do not intend to steal keys but rather to disrupt key distribution communication. This makes it difficult for the sender and receiver to maintain efficient key distribution communication, resulting in reduced service availability and a significant decrease in overall communication quality. Summary of the Invention

[0004] This application provides a data quality analysis method for quantum communication data transmission processes to solve the aforementioned technical problems.

[0005] In a first aspect, this application provides a data quality analysis method for quantum communication data transmission processes, the method comprising: Obtain the real-time key negotiation dataset, analyze the real-time key negotiation dataset, and determine the real-time negotiation bit error rate; The real-time negotiation bit error rate is compared with the protocol bit error rate security threshold. Based on the comparison result, it is determined whether the interference-driven key resilience reconstruction mechanism needs to be activated. If the interference-driven key resilience reconstruction mechanism needs to be activated, then according to the interference-driven key resilience reconstruction mechanism, trap filtering and key fragment multiplexing splicing processing are performed on the surviving bits in several key negotiation processes to determine and output the resilience reconstruction key.

[0006] This scheme tracks the real-time bit error rate during quantum key distribution and uses this as a criterion to introduce an interference-driven resilient key reconstruction mechanism. Utilizing a triple-cascaded key reconstruction mechanism of real-time bit error rate analysis, resilient activation decision, and trap filtering reconstruction, a resilient reconstructed key is obtained. This enables both communicating parties to efficiently negotiate a secure key even under continuous high-intensity communication interference from a third party, improving the robustness of the quantum key distribution service. Furthermore, it ensures high availability even when attackers aim to disrupt key distribution communication purely for the purpose of interference rather than key theft, thereby improving the quality of quantum communication.

[0007] Optionally, analyzing the real-time key negotiation dataset to determine the real-time negotiation error rate includes: The real-time key negotiation dataset includes a unified index dataset, a sender basis vector sequence, a receiver basis vector sequence, and a negotiation sampling quantity; Based on the unified index dataset, basis vector consistency matching analysis is performed on the sender basis vector sequence and the receiver basis vector sequence, and the corresponding indexes under the basis vector consistency case are recorded to construct a basis vector consistency index set; Based on the negotiated sampling quantity, a corresponding number of indexes are randomly selected from the basis vector consistency index set to determine the sampling index set; Based on the sampling index set, the number of erroneous bits is determined by publicly comparing the bit value corresponding to each index in the sampling index set through a preset classic authentication channel. The ratio of the number of erroneous bits to the number of negotiated samples is used as the real-time negotiation bit error rate.

[0008] This scheme filters out a subset of data with consistent basis vectors based on the basis vector consistency index set, and then quickly quantifies the number of error bits through random sampling to assess the scale of error bits and obtain the real-time negotiation bit error rate. Compared with the traditional scheme, the bit error assessment is advanced to the middle of the negotiation, which provides a critical time window for activating the subsequent key reconstruction mechanism. Moreover, only a small number of sampled bits are publicly compared (rather than all of them), which greatly reduces the classical channel load and reduces the risk and scale of data leakage.

[0009] Optionally, comparing the real-time negotiation bit error rate with the protocol bit error rate security threshold, and determining whether to activate the interference-driven key resilience reconstruction mechanism based on the comparison result, includes: The protocol error rate security threshold is the protocol security threshold corresponding to the QBER (Quantum Bit Error Rate) value specified in the quantum key distribution protocol currently used by both communicating parties; The real-time negotiation bit error rate is compared with the protocol bit error rate security threshold. If the real-time negotiation bit error rate is less than the protocol bit error rate security threshold, the classic QKD mechanism (Quantum Key Distribution) is adopted. If the real-time negotiation bit error rate is greater than the protocol bit error rate security threshold, then the interference-driven key resilience reconstruction mechanism is activated.

[0010] This scheme uses the real-time negotiation error rate as the switching benchmark. Based on the classic QKD mechanism, when the real-time negotiation error rate exceeds the corresponding protocol's error rate safety threshold, an interference-driven key resilience reconstruction mechanism is introduced to ensure the availability of the key generation service under high-intensity interference. This forms a dual-path response of "classical QKD + interference-driven resilience reconstruction", which ensures the high availability of the quantum communication-based key generation service under both low and high negotiation error rates.

[0011] Optionally, the interference-driven key resilience reconstruction mechanism includes: Based on the sampling index set, several basis vectors corresponding to the sampling index set are removed from the sender basis vector sequence and the receiver basis vector sequence to determine the pre-screened basis vector set; Analyze the pre-screened basis set, and filter the bit data in the sender basis sequence and the receiver basis sequence that have the same basis and the same bit value to form a real-time surviving bit dataset; Based on the quantum bit trap detection strategy, the real-time surviving bit dataset is subjected to bit trap filtering processing to determine the dynamic effective key fragment dataset and the bit trap ratio distribution information set; Based on the trap ratio distribution information set and the bit trap ratio distribution information set, according to the bit trap ratio corresponding to each valid key fragment in the valid key fragment dataset, a hierarchical security amplification strategy is executed to determine the compressed dynamic key fragment dataset. Based on the limited reuse strategy, several key fragments are reused and spliced ​​according to the compressed dynamic key fragment dataset to generate the resilient reconstruction key.

[0012] This scheme obtains a real-time surviving bit dataset by filtering the sampling index set. Combining the quantum bit trap detection strategy, the hierarchical security amplification strategy, and the limited multiplexing strategy, an interference-driven key resilience reconstruction mechanism is formed to ensure the efficiency of key negotiation and the security of key under high-intensity interference. This enables the quantum communication-based key negotiation process to still obtain a secure key when faced with attacks aimed at interrupting communication.

[0013] Optionally, the qubit trap detection strategy includes: Based on the decoy state injection strategy, according to the real-time negotiated bit error rate, the proportion of dynamic pulses that the decoy state pulses need to be in the total transmitted pulses is determined, and according to the proportion of dynamic pulses, the corresponding proportion of the decoy state pulses is generated to construct a decoy state pulse dataset. Based on the decoy state pulse dataset, the precise arrival timestamps of all successfully detected pulses are counted to construct a pulse timestamp distribution dataset; Based on the decoy state pulse dataset, the difference in detection rate between the theoretical detection rate and the actual detection rate of the decoy state pulse is quantified; Based on the timestamp correlation analysis strategy, the pulse timestamp distribution dataset is analyzed according to the detection rate difference to determine the high-risk trap pulse information and the proportion of high-risk traps in the current negotiation process; Based on the high-risk trap pulse information, the bit data under the corresponding index in the real-time surviving bit data set is removed, and the remaining bit data is used as the valid key fragment for the current negotiation process; By integrating the effective key fragments and the proportion of high-risk traps from each negotiation process, the dynamic effective key fragment dataset and the bit trap proportion distribution information set are constructed respectively.

[0014] This scheme significantly improves the accuracy of trap pulse detection by utilizing the dual correlation analysis of decoy state response anomalies and timestamp distribution distortion, avoiding the misjudgment of legitimate pulses. It adaptively adjusts the proportion of decoy states according to the degree of bit error rate exceeding the limit, saving resources under low interference and strengthening defense under high interference, improving the system's energy efficiency ratio, effectively eliminating trap pulses injected by attackers, ensuring the purity of surviving bits, and providing high-quality input for subsequent key fragment reuse.

[0015] Optionally, the decoy state injection strategy includes: Two types of pulses with varying light intensity levels are defined: signal state pulses and decoy state pulses. The intensity of the signal state pulse is greater than the intensity of the decoy state pulse; Both the signal state pulse and the decoy state pulse are emitted through the same laser pulse emitter; The sum of the intensity of the signal state pulse and the intensity of the decoy state pulse is less than the maximum allowable power of the laser pulse emitter; During the transmission of the signal state pulse and the decoy state pulse, a pulse scheduling strategy based on chaotic sequences is adopted to ensure that the transmission order of the signal state pulse and the decoy state pulse satisfies an aperiodic pseudo-random distribution in the time domain, thereby preventing attackers from inferring the pulse type through time sequence patterns. The ratio of the real-time negotiated bit error rate to the protocol bit error rate security threshold is used as the bit error rate excess ratio. Based on the bit error rate excess ratio, the proportion of the decoy state pulse in the total pulse is linearly increased to determine the dynamic pulse proportion.

[0016] This solution utilizes a dynamic decoy state ratio mechanism to significantly increase the density of decoy state pulses in high error rate scenarios, making attacks more easily detectable. It also reduces invalid probes in low interference scenarios and breaks the regularity of transmission timing through chaotic sequence scheduling, making it impossible for attackers to specifically evade detection. Even in the event of high-intensity interference, the key distribution process can continue, ensuring service availability.

[0017] Optionally, the timestamp association analysis strategy includes: Based on the classic channel-synchronized atomic clock timing reference, the timestamp data in the pulse timestamp distribution dataset is uniformly aligned to determine the aligned pulse timestamp dataset. Based on the aligned pulse timestamp dataset, the time intervals corresponding to all adjacent successful detection pulses are counted to construct a time interval distribution dataset; Analyze the time interval distribution dataset, define the time intervals within the time interval distribution dataset that are greater than 3 times the standard deviation of the historical average time interval as abnormal intervals, and construct an abnormal interval distribution dataset; If the successful detection pulse is located within any of the abnormal intervals in the abnormal interval distribution dataset, and both pulses before and after the current successful detection pulse are successfully detected, then the current successful detection pulse is taken as a high-risk trap pulse, and the high-risk trap pulse information is constructed. Based on the proportion of high-risk trap pulses among all successful detection pulses, and combined with the detection rate difference, a composite weighted evaluation of the trap bit proportion is performed to determine the proportion of high-risk traps.

[0018] This scheme utilizes a timestamp micro-anomaly detection mechanism to identify carefully disguised trap pulses by attackers, overcoming the limitations of traditional strength detection methods, improving the accuracy of trap pulse detection, reducing the amount of invalid key discarded by accurately locating abnormal pulses, improving the utilization rate of surviving bits, and supporting the efficient reuse and splicing of subsequent key fragments.

[0019] Optionally, the layered security amplification strategy includes: Based on the proportion of high-risk traps corresponding to each valid key fragment, query the preset trap ratio-compression ratio mapping information to determine the key compression ratio corresponding to each valid key fragment; The proportion of high-risk traps is positively correlated with the corresponding key compression ratio; Based on the total length of bit data corresponding to each valid key fragment, a length-expandable hash function is used to perform preliminary homogenization processing on each valid key fragment to determine the key homogenization processing result. Based on the key compression ratio corresponding to each valid key fragment, a quantum-resistant hash function is used to perform key compression processing on the key homogenization processing result corresponding to each valid key fragment, thereby determining the compressed dynamic key fragment dataset.

[0020] This solution quantifies attack intensity in real time based on the proportion of high-risk traps and dynamically adjusts the compression ratio to precisely match the security amplification strength with the severity of interference. By using layered security amplification processing, it avoids "one-size-fits-all" compression, allowing low-risk fragments to retain more effective bits and high-risk fragments to be compressed more effectively. Compared with traditional fixed compression strategies, it significantly reduces residual security risks in high-interference scenarios. By maximizing the use of low-pollution fragments, it reduces the number of negotiation interruptions triggered by insufficient key length, ensuring that the communication link continues to provide services in interference environments.

[0021] Optionally, the limited reuse strategy includes: Key length constraint rule: The total length of the effective key fragments spliced ​​together in multiple rounds shall not exceed a preset key length threshold; Negotiation round constraint rules: Based on the service response speed requirements of both communicating parties, a maximum number of negotiation rounds is set. After each round of key fragment multiplexing and splicing processing is completed, the round counter is automatically incremented. When the round counter value is equal to the maximum number of negotiation rounds, the currently spliced ​​key fragment is used as the resilient reconstruction key.

[0022] This scheme utilizes key length constraint rules and negotiation round constraint rules to constrain the length and negotiation rounds of the resilient reconstruction key obtained by splicing key fragments, thereby achieving a good balance between key generation efficiency and key security. This ensures the basic efficiency of the final resilient reconstruction key construction, avoids the key negotiation process from falling into an infinite loop, and introduces uncertainty into the construction time of the resilient reconstruction key, further improving the security of the resilient reconstruction key.

[0023] Optionally, the method further includes: Key fragment lifecycle management rules: After each valid key fragment is generated, a lifecycle timer is created and started for it; If the valid key fragment is not used within the preset expiration period, the corresponding valid key will be automatically discarded. Interruption recovery rules: When communication between the two parties is interrupted due to interference from the attacker, the number of splicing rounds and the key length that have been completed are recorded. After the link is restored, the key reuse splicing is continued from the nearest valid checkpoint.

[0024] This solution utilizes key fragment lifecycle management rules to constrain the lifecycle of valid key fragments, thereby preventing attackers from launching correlation analysis attacks against key fragments by exploiting the lifecycle time difference window. At the same time, it uses interruption recovery rules to reduce the key generation time after communication interruption, ensuring that the key generation service maintains high availability under high-intensity continuous interference. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram illustrating an application scenario provided in one embodiment of this application; Figure 2 A flowchart illustrating a data quality analysis method for a quantum communication data transmission process, provided as an embodiment of this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0028] Furthermore, the term "and / or" in this article 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, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0029] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0030] Existing quantum key distribution technologies are prone to sharp declines in key distribution efficiency or even interruption of key distribution communication when faced with high-intensity interference from attackers who do not intend to steal keys but rather to disrupt key distribution communication. This makes it difficult for the sender and receiver to maintain efficient key distribution communication, resulting in reduced service availability and a significant decrease in overall communication quality.

[0031] Based on this, this application provides a data quality analysis method for quantum communication data transmission. It tracks the real-time bit error rate during quantum key distribution and uses this as a criterion to introduce an interference-driven resilient key reconstruction mechanism. Utilizing a triple-cascaded key reconstruction mechanism of real-time bit error rate analysis, resilient activation decision, and trap filtering reconstruction, a resilient reconstructed key is obtained. This enables both communicating parties to efficiently negotiate a secure key even under continuous high-intensity communication interference from a third party, improving the robustness of the quantum key distribution service. Furthermore, it ensures high availability even when attackers aim to disrupt key distribution communication purely for the purpose of interference rather than key theft, thereby improving the quality of quantum communication.

[0032] Figure 1 This is a schematic diagram illustrating an application scenario provided by this application. In the process of quantum communication key distribution, the method provided in this application enables the quantum key distribution service to maintain high availability even when facing high-intensity interference from attackers whose purpose is not to steal keys but purely to disrupt key distribution communication, thereby improving the quality of quantum communication.

[0033] Specifically, the method of this application is applied to any server controlled by both communicating parties. This server communicates with the quantum communication device, acquires and analyzes the real-time key negotiation dataset provided by the quantum communication device, tracks the real-time bit error rate during the quantum key distribution process, and uses this as a basis for judgment. An interference-driven resilient key reconstruction mechanism is introduced, utilizing a triple-cascaded key reconstruction mechanism of real-time bit error rate analysis, resilient activation decision, and trap filtering reconstruction to derive a resilient reconstructed key. This enables the communicating parties to efficiently negotiate a secure key even under continuous high-intensity communication interference from a third party, improving the robustness of the quantum key distribution service. This ensures that the quantum key distribution service maintains high availability even when facing high-intensity interference from attackers who do not intend to steal keys but rather to purely disrupt key distribution communication, thereby improving the quality of quantum communication. Specific implementation methods can be found in the following embodiments.

[0034] Figure 2 This is a flowchart illustrating a data quality analysis method for a quantum communication data transmission process according to an embodiment of this application. The method of this embodiment can be applied to servers in the above scenarios. Figure 2 As shown, the method includes: S201. Obtain the real-time key negotiation dataset, analyze the real-time key negotiation dataset, and determine the real-time negotiation bit error rate.

[0035] The real-time key negotiation dataset can be the raw data set of the communication between the two parties during the quantum key distribution (QKD) process, which comes from the real-time transmission logs of the quantum communication device.

[0036] The real-time negotiation error rate can be the qubit error rate of the current key negotiation process, quantized by sampling comparison.

[0037] Specifically, existing quantum key distribution (QKD) technologies face a bottleneck: when attackers implement high-intensity interference (such as photon number splitting attacks or strong light blinding attacks), they may not aim to steal the key, but rather disrupt the key negotiation process by injecting noise pulses or altering timestamps. Such attacks lead to the following problems: interference pulses mix with legitimate signals, causing the basis vector matching error rate to far exceed the protocol's security threshold (typically >11%), resulting in an uncontrollable spike in the bit error rate, triggering the interruption mechanism of traditional QKD, and causing key distribution failure; frequent interruptions force the communicating parties to repeatedly restart the negotiation process, causing key generation efficiency to decline exponentially, failing to meet real-time encryption requirements; negotiated bit data is discarded because a complete key has not been established, resulting in low utilization of quantum channel resources. When faced with the problems caused by these attacks, existing technologies typically employ channel switching and isolation measures for communication negotiation reconstruction. This approach drastically reduces key negotiation efficiency and makes the success or failure of key negotiation highly uncertain, significantly reducing the availability of quantum key distribution services.

[0038] Attacks aimed at disrupting communication have the most direct impact on quantum key distribution by causing a sharp increase in the quantum error rate. Therefore, tracking and evaluating the quantum error rate during key negotiation between the two communicating parties is crucial for determining whether the current communication process is subject to continuous high-intensity interference. By quantitatively analyzing the real-time key negotiation dataset, the ratio between the current number of erroneous bits and the total number of bits, i.e., the real-time negotiation error rate, is obtained, providing a scientific data foundation for subsequent analysis of the key negotiation process under high error rates.

[0039] S202. Compare the real-time negotiated bit error rate with the protocol bit error rate security threshold, and determine whether it is necessary to activate the interference-driven key resilience reconstruction mechanism based on the comparison results.

[0040] The protocol error rate security threshold can be the maximum qubit error rate specified in the quantum key distribution protocol used by both communicating parties.

[0041] Interference-driven key resilience reconstruction mechanisms can be strategies for reconstructing usable keys using surviving bits from different negotiation rounds under high-voltage interference.

[0042] Specifically, due to the uncertainty and non-cloning properties of qubits, the attacker's contamination rate of qubits cannot reach 100%. This means that even under high-intensity interference, both communicating parties can still obtain some surviving qubit data that has not been contaminated by the attacker during each key negotiation process. Existing technologies automatically discard all qubit data in the current negotiation and restart the negotiation process when the qubit error rate exceeds the corresponding protocol's error rate threshold. This is the key reason for the sharp decline in key negotiation efficiency under high-intensity interference. However, this solution recognizes that under continuous high-intensity attacks from the attacker, the surviving qubit data in each negotiation process itself has strong unpredictability. This strong unpredictability is precisely what allows for the number of surviving qubits to increase. To ensure high-level security, surviving bits are essential for becoming the key. Furthermore, considering the uncertainty of the number of surviving qubits in each negotiation process, using surviving bits from a single negotiation as the key risks resulting in an excessively short key length. Therefore, by activating an interference-driven key resilience reconstruction mechanism—which uses surviving bits to inversely convert high-intensity interference into resources that enhance key unpredictability—and combining surviving bit data from multiple negotiation processes to obtain the final key, the mechanism ensures key security while improving the key negotiation efficiency of both parties under high-intensity interference. This avoids the sharp decline in negotiation efficiency caused by the existing "discard interference" mindset.

[0043] S203. If it is necessary to activate the interference-driven key resilience reconstruction mechanism, then according to the interference-driven key resilience reconstruction mechanism, trap filtering and key fragment multiplexing splicing are performed on the surviving bits in several key negotiation processes to determine and output the resilience reconstruction key.

[0044] The key negotiation process can be a communication process in which two parties use quantum key distribution technology to construct a data encryption key.

[0045] Surviving bits can be the original key bits that, despite interference from the attacker, still maintain basis consistency and have not been sampled for public comparison.

[0046] Trap filtering can be a process based on qubit trap detection strategies to identify and eliminate high-risk interference pulse-related bits.

[0047] Key fragment multiplexing and splicing can be the process of combining valid key fragments negotiated in multiple rounds into a complete key.

[0048] A resilient reconstruction key can be a key that is recognized by both communicating parties and obtained through a interference-driven key resilient reconstruction mechanism.

[0049] Specifically, in the process of generating a key using surviving bits from the attacker's interference, if the attacker becomes aware of this process, they may use this mechanism to inject some trap bits during the attack, causing some trap bits known to the attacker to be mixed into the surviving bits, thus leading to a collapse in key security. Therefore, the surviving bits need to undergo further trap bit filtering to identify and remove the trap bits known to the attacker, ensuring the security of the surviving bits. Then, by reusing and splicing the filtered surviving bits from multiple negotiation processes, a resilient reconstruction key is constructed, enabling both parties to quickly obtain a secure key under high-intensity interference, thereby improving the security of subsequent data encryption processes based on the resilient reconstruction key.

[0050] This scheme tracks the real-time bit error rate during quantum key distribution and uses this as a criterion to introduce an interference-driven resilient key reconstruction mechanism. Utilizing a triple-cascaded key reconstruction mechanism of real-time bit error rate analysis, resilient activation decision, and trap filtering reconstruction, a resilient reconstructed key is obtained. This enables both communicating parties to efficiently negotiate a secure key even under continuous high-intensity communication interference from a third party, improving the robustness of the quantum key distribution service. Furthermore, it ensures high availability even when attackers aim to disrupt key distribution communication purely for the purpose of interference rather than key theft, thereby improving the quality of quantum communication.

[0051] In some embodiments, the real-time key negotiation dataset includes a unified index dataset, a sender basis vector sequence, a receiver basis vector sequence, and a negotiation sampling quantity. Based on the unified index dataset, basis vector consistency matching analysis is performed on the sender and receiver basis vector sequences, and the corresponding indices under consistent basis vector conditions are recorded to construct a basis vector consistency index set. Based on the negotiation sampling quantity, a corresponding number of indices in the basis vector consistency index set are randomly sampled to determine a sampling index set. Based on the sampling index set, the bit values ​​corresponding to each index in the sampling index set are publicly compared through a preset classic authentication channel to determine the number of erroneous bits. The ratio of the number of erroneous bits to the negotiation sampling quantity is used as the real-time negotiation bit error rate.

[0052] A unified index dataset can be a unique position identifier (such as a time slot number) that marks each qubit in the transmission sequence, generated by the timing controller at the quantum transmitter.

[0053] The sender basis sequence can be a measurement basis (such as the X basis or the Z basis) randomly selected by the sender for each qubit, implemented by a quantum state modulator.

[0054] The receiver basis sequence can be a measurement basis randomly selected by the receiver for the received qubit, generated by the receiver basis selector.

[0055] The number of samples to be negotiated can be the number of bits to be publicly compared that are agreed upon by both parties in advance, and determined through classic channel negotiation (such as the protocol default value of 20% of the total number of bits).

[0056] Basis consistency matching analysis can compare whether the basis vectors at the same index position in the basis vector sequences of the sender and receiver are consistent (e.g., if both parties choose the X basis vector, the basis vectors are consistent).

[0057] A basis-consistent index set can be a set of index positions that record all basis-consistent bits.

[0058] The sampling index set can be a subset of the indexes that is randomly selected from the basis-consistent index set, which is a specified number (negotiated sampling number).

[0059] The default classic authentication channel can be a classic communication channel (such as the TLS protocol) that is authenticated and encrypted, used for secure transmission of sampled bit values.

[0060] The number of erroneous bits can be the number of bits in the sampled index set that do not match.

[0061] The real-time negotiation bit error rate (RBER) is the ratio of the number of erroneous bits to the number of negotiation samples, reflecting the degree of interference in the current channel.

[0062] Specifically, a unified index dataset is invoked to align the temporal positions of the basis vector sequences of both communicating parties. The indexes are traversed, and the basis vector types are compared. If the basis vectors of both parties are the same (e.g., both are X basis vectors), the index is added to the basis vector consistency index set. Based on the number of negotiated samples (e.g., 100), a quantum random number generator is used to randomly select the corresponding index from the basis vector consistency index set to generate a sampling index set. The two communicating parties exchange the original bit values ​​of each index in the sampling index set through a preset classical authentication channel. The number of inconsistent bits is counted and recorded as the number of error bits. The real-time negotiation bit error rate is quantified (real-time negotiation bit error rate = number of error bits / number of negotiated samples). Based on the basis vector consistency index set, a subset of data with consistent basis vectors is selected. Then, the number of error bits is quickly quantified through random sampling to assess the scale of error bits and obtain the real-time negotiation bit error rate. Compared with the traditional scheme, the bit error assessment is advanced to the middle of the negotiation, which provides a critical time window for activating the subsequent key reconstruction mechanism. Moreover, only a small number of sampled bits are publicly compared (not all of them), which greatly reduces the classical channel load and reduces the risk and scale of data leakage.

[0063] This scheme filters out a subset of data with consistent basis vectors based on the basis vector consistency index set, and then quickly quantifies the number of error bits through random sampling to assess the scale of error bits and obtain the real-time negotiation bit error rate. Compared with the traditional scheme, the bit error assessment is advanced to the middle of the negotiation, which provides a critical time window for activating the subsequent key reconstruction mechanism. Moreover, only a small number of sampled bits are publicly compared (rather than all of them), which greatly reduces the classical channel load and reduces the risk and scale of data leakage.

[0064] In some embodiments, the protocol error rate security threshold is the protocol security threshold corresponding to the QBER (Quantum Bit Error Rate) value specified in the quantum key distribution protocol used by the current communicating parties. The real-time negotiation error rate is compared with the protocol error rate security threshold. If the real-time negotiation error rate is less than the protocol error rate security threshold, the classical QKD (Quantum Key Distribution) mechanism is used. If the real-time negotiation error rate is greater than the protocol error rate security threshold, the interference-driven key resilience reconstruction mechanism is activated.

[0065] The classic QKD mechanism can be a standard quantum key distribution process, including basic steps such as basis vector comparison, error checking, and security amplification. It follows the corresponding communication standard, is implemented by the firmware layer of the quantum communication device, and is activated when the error rate is below the security threshold to ensure efficient key generation in a low-interference environment.

[0066] Specifically, when the real-time error rate exceeds a fixed threshold (e.g., 11%), traditional quantum key distribution schemes directly terminate negotiation. When faced with attacks aimed at paralyzing communication services, differentiated response strategies are needed to ensure the availability of the key generation service. By using the real-time negotiation error rate as the switching benchmark, and based on the classical QKD mechanism, when the real-time negotiation error rate exceeds the corresponding protocol's error rate safety threshold, an interference-driven key resilience reconstruction mechanism is introduced to ensure the availability of the key generation service under high-intensity interference. This forms a dual-path response of "classical QKD + interference-driven resilience reconstruction," enabling the high availability of quantum communication-based key generation services to be well guaranteed under both low and high negotiation error rates.

[0067] This scheme uses the real-time negotiation error rate as the switching benchmark. Based on the classic QKD mechanism, when the real-time negotiation error rate exceeds the corresponding protocol's error rate safety threshold, an interference-driven key resilience reconstruction mechanism is introduced to ensure the availability of the key generation service under high-intensity interference. This forms a dual-path response of "classical QKD + interference-driven resilience reconstruction", which ensures the high availability of the quantum communication-based key generation service under both low and high negotiation error rates.

[0068] In some embodiments, based on a sampling index set, several basis vectors corresponding to the sampling index set are removed from the sender's basis vector sequence and the receiver's basis vector sequence to determine a pre-screened basis vector set; the pre-screened basis vector set is analyzed to select bit data with the same basis vectors and bit values ​​in the sender's basis vector sequence and the receiver's basis vector sequence to form a real-time surviving bit dataset; based on a quantum bit trap detection strategy, bit trap filtering processing is performed on the real-time surviving bit dataset to determine a dynamic effective key fragment dataset and a bit trap ratio distribution information set; based on the trap ratio distribution information set and the bit trap ratio distribution information set, a hierarchical security amplification strategy is executed according to the bit trap ratio corresponding to each effective key fragment in the effective key fragment dataset to determine a compressed dynamic key fragment dataset; based on a finite multiplexing strategy, several key fragments are multiplexed and spliced ​​according to the compressed dynamic key fragment dataset to generate a resilient reconstruction key.

[0069] The pre-screened basis set can be the set of remaining basis vectors after removing the basis vectors corresponding to the sampling index set from the basis vector sequences of the sender and receiver.

[0070] A real-time surviving bit dataset can be a set of bit data in a pre-selected basis set that has the same basis vectors and the same bit values.

[0071] Quantum bit trap detection strategies can be defense mechanisms that identify and filter trap bits (such as forged photons) implanted by attackers.

[0072] A dynamic valid key fragment dataset can be a set of trusted bit fragments retained after trap detection, with each fragment corresponding to a single negotiation cycle.

[0073] The bit trap proportion distribution information set can be a dataset that records the proportion of trap bits detected during the generation of each valid key fragment.

[0074] Layered security amplification strategy can be a key security enhancement process that dynamically adjusts the key compression strength according to the trap ratio.

[0075] The compressed dynamic key fragment dataset can be a set of standardized key fragments after hierarchical security amplification processing.

[0076] A finite reuse strategy can be a set of rules for splicing key fragments under constraints.

[0077] Specifically, during high-intensity interference, generating a data encryption key using surviving keys from multiple negotiation processes requires addressing the following core issues: surviving bits may contain bit traps; existing unified security amplification mechanisms are not applicable to fragmented key security amplification; and the constraints of the reuse mechanism need to ensure a balance between efficiency and security. If the real-time negotiation bit error rate is greater than or equal to the protocol's bit error rate security threshold, it indicates that the current key negotiation process is under high-intensity interference. At this point, the interference-driven key resilience reconstruction mechanism is activated, executing the following multiple strategies: The sampling index set is invoked, and the corresponding index basis vectors are removed from the sender's and receiver's basis vector sequences (the bit values ​​of the corresponding indexes in the sampling index set have already been compared in the public channel, posing a risk of exposure; therefore, this portion of the basis vector data should not be included in the key bit data), generating a pre-screened basis vector set containing only unexposed basis vectors; the pre-screened basis vector set is iterated, locating the index positions where all basis vectors are consistent, and comparing the sender's and receiver's values ​​at those positions. A real-time surviving bit dataset is constructed by retaining bits with the same value. A quantum bit trap detection strategy is activated to remove bits corresponding to trap pulse indices from the surviving bit dataset, resulting in a dynamic effective key fragment dataset and a bit trap ratio distribution information set. Based on the bit trap ratio distribution information set, a compression ratio is assigned to each key fragment (the higher the trap ratio, the greater the compression ratio), and a corresponding hash algorithm is used to perform labeled compression processing on the key fragments, resulting in a standardized compressed dynamic key fragment dataset. Finally, a finite reuse strategy is invoked to generate a resilient reconstruction key under finite rounds and key length constraints.

[0078] This scheme obtains a real-time surviving bit dataset by filtering the sampling index set. Combining the quantum bit trap detection strategy, the hierarchical security amplification strategy, and the limited multiplexing strategy, an interference-driven key resilience reconstruction mechanism is formed to ensure the efficiency of key negotiation and the security of key under high-intensity interference. This enables the quantum communication-based key negotiation process to still obtain a secure key when faced with attacks aimed at interrupting communication.

[0079] In some embodiments, based on a decoy injection strategy, the proportion of dynamic pulses that decoy pulses need to make in the total transmitted pulses is determined according to the real-time negotiation bit error rate. Based on this dynamic pulse proportion, decoy pulses of a corresponding proportion are generated, and a decoy pulse dataset is constructed. Based on the decoy pulse dataset, the precise arrival timestamps of all successful detection pulses are statistically analyzed, and a pulse timestamp distribution dataset is constructed. Based on the decoy pulse dataset, the detection rate difference between the theoretical and actual detection rates of the decoy pulses is quantified. Based on a timestamp correlation analysis strategy, the pulse timestamp distribution dataset is analyzed based on the detection rate difference to determine the high-risk trap pulse information and the proportion of high-risk traps in the current negotiation process. Based on the high-risk trap pulse information, bit data under the corresponding index in the real-time surviving bit dataset is removed, and the remaining bit data is used as the valid key fragments for the current negotiation process. The valid key fragments and the proportion of high-risk traps in each negotiation process are integrated to construct a dynamic valid key fragment dataset and a bit trap proportion distribution information set, respectively.

[0080] Deceived pulses can be interference pulse signals used to confuse attackers in their judgment of key signals.

[0081] The dynamic pulse ratio can be the real-time proportion of decoy pulses in the total transmitted pulses, and this proportion is dynamically adjusted according to the degree to which the negotiation bit error rate exceeds the limit.

[0082] A successful detection pulse can be a decoy pulse that the attacked party successfully detects.

[0083] A pulse timestamp distribution dataset can be a collection that records the precise arrival timestamps of all successfully detected pulses, used to analyze the temporal regularity of pulse transmission.

[0084] The theoretical detection rate can be the expected probability of successfully detecting a decoy pulse in an ideal, attack-free environment.

[0085] The actual detection rate can be the statistical probability that a decoy pulse is successfully detected in actual communication.

[0086] The detection rate difference can be the probability difference between the theoretical detection rate and the actual detection rate.

[0087] High-risk trap pulse information can be a set of pulse indices that are determined to be highly likely to be forged or interfered with by the attacker.

[0088] The high-risk trap percentage can be the proportion of high-risk trap pulses to the total number of successfully detected pulses.

[0089] Specifically, attackers can forge pulse timestamps or inject delayed pulses, making it difficult for traditional methods to distinguish legitimate pulses from "trap pulses" forged by attackers. This solution utilizes a custom decoy injection strategy, linearly increasing the proportion of decoy pulses based on the ratio of real-time negotiated bit error rate to a security threshold (bit error rate exceeding the limit). It records the precise arrival timestamps of all successful detection pulses, aligns the timestamp data using the atomic clocks of both communicating parties via a classic channel to eliminate clock drift errors, and calculates the actual detection rate of decoy pulses (number of successful detections / total number of transmissions). This is compared with the theoretical detection rate (calculated based on channel loss), and the difference is taken as the detection rate difference. The larger the value, the stronger the interference from the attacker. The difference in detection rate is positively correlated with the proportion of trap bits (used to improve the accuracy of trap bit size assessment). Based on this, a custom timestamp correlation analysis strategy is further combined to obtain the high-risk trap pulse information and the proportion of high-risk traps in the current negotiation process. Then, the bit data corresponding to the high-risk trap pulses are removed from the real-time surviving bit dataset. The remaining bit data is used as the effective key fragments in the current negotiation process, and the proportion of high-risk traps is recorded. By integrating the effective key fragments and the proportion of high-risk traps in each negotiation process, a dynamic effective key fragment dataset and a bit trap ratio distribution information set are constructed respectively.

[0090] This scheme significantly improves the accuracy of trap pulse detection by utilizing the dual correlation analysis of decoy state response anomalies and timestamp distribution distortion, avoiding the misjudgment of legitimate pulses. It adaptively adjusts the proportion of decoy states according to the degree of bit error rate exceeding the limit, saving resources under low interference and strengthening defense under high interference, improving the system's energy efficiency ratio, effectively eliminating trap pulses injected by attackers, ensuring the purity of surviving bits, and providing high-quality input for subsequent key fragment reuse.

[0091] In some embodiments, two types of pulses with different intensity levels are defined: signal pulses and decoy pulses. The intensity of the signal pulse is greater than that of the decoy pulse. Both the signal pulse and the decoy pulse are emitted through the same laser pulse transmitter. The sum of the intensities of the signal pulse and the decoy pulse is less than the maximum allowable power of the laser pulse transmitter. During the emission of the signal pulse and the decoy pulse, a pulse scheduling strategy based on chaotic sequences is adopted to ensure that the emission order of the signal pulse and the decoy pulse satisfies an aperiodic pseudo-random distribution in the time domain, preventing attackers from inferring the pulse type through temporal patterns. The ratio of the real-time negotiated bit error rate to the protocol bit error rate safety threshold is used as the bit error rate over-limit ratio. Based on the bit error rate over-limit ratio, the proportion of the decoy pulse in the total pulses is linearly increased to determine the dynamic pulse proportion.

[0092] The signal state pulse can be a quantum pulse with high light intensity, used to carry effective key information, and its intensity must be sufficient to ensure that the receiver can detect it stably.

[0093] A laser pulse transmitter can be a core hardware component in quantum communication devices that emits light pulses. It needs to support dual-intensity pulse output and adjustable power.

[0094] The maximum permissible power can be the maximum optical power threshold at which the laser pulse transmitter can operate safely. The sum of the intensities of the signal state and the decoy state pulses must be lower than this value to avoid communication interruption caused by equipment malfunction.

[0095] A pulse scheduling strategy based on chaotic sequences can be a strategy that controls the pulse emission order based on an unpredictable, non-periodic random number sequence generated by a chaotic system.

[0096] An aperiodic pseudo-random distribution can be characterized by pulse emission intervals that have no fixed pattern and whose distribution characteristics conform to pseudo-randomness, making it impossible for attackers to predict the pulse type through statistics.

[0097] The bit error rate exceeding the limit can be the multiple by which the real-time negotiated bit error rate exceeds the protocol security threshold, quantifying the severity of the current interference.

[0098] Linear incremental processing can be a process of dynamically adjusting the proportion of decoy pulses according to the linear proportional relationship between the percentage of bit error rate exceeding the limit and the proportion of decoy pulses.

[0099] Specifically, since the attacker's interference behavior is dynamic, if a fixed decoy state ratio is used, the bit trap detection mechanism based on the decoy state will be unable to cover the attacker's dynamic attack. Therefore, the decoy state ratio needs to be dynamically changed with the attacker's interference intensity. At the same time, it is necessary to prevent attackers from identifying the pulse type by analyzing the emission patterns of decoy state pulses and signal state pulses. Two types of pulses with varying intensity levels are defined: signal pulses and decoy pulses. The intensity of the signal pulse (e.g., 1.0 μW) and the intensity of the decoy pulse (e.g., 0.2 μW) are configured, ensuring that their sum is lower than the maximum allowable power of the laser pulse transmitter (e.g., 1.5 μW). A chaotic sequence generation algorithm (e.g., Lorenz equation) is preloaded to generate a non-periodic random number sequence. This chaotic sequence is mapped to a pulse type decision sequence: when the value is greater than a preset threshold, a decoy state is emitted; otherwise, a signal state is emitted. The pulse emission time is scheduled according to the decision sequence to ensure that the interval between adjacent pulses is random and non-periodic. Simultaneously, the bit error rate exceeding the limit ratio is calculated in real time: exceeding the limit ratio = (real-time negotiated bit error rate - protocol security threshold) / protocol security threshold. The dynamic pulse proportion is determined according to a linear relationship: decoy state proportion = base proportion + exceeding the limit ratio × adjustment coefficient (obtained through experimental fitting).

[0100] This solution utilizes a dynamic decoy state ratio mechanism to significantly increase the density of decoy state pulses in high error rate scenarios, making attacks more easily detectable. It also reduces invalid probes in low interference scenarios and breaks the regularity of transmission timing through chaotic sequence scheduling, making it impossible for attackers to specifically evade detection. Even in the event of high-intensity interference, the key distribution process can continue, ensuring service availability.

[0101] In some embodiments, based on the classic channel synchronization atomic clock timing benchmark, the timestamp data in the pulse timestamp distribution dataset is uniformly aligned to determine the aligned pulse timestamp dataset. Based on the aligned pulse timestamp dataset, the time intervals corresponding to all adjacent successful detection pulses are statistically analyzed to construct a time interval distribution dataset. The time interval distribution dataset is analyzed, and the time intervals within the dataset where the time interval is greater than three times the standard deviation of the historical average time interval are defined as abnormal intervals, thus constructing an abnormal interval distribution dataset. If a successful detection pulse is located within any abnormal interval in the abnormal interval distribution dataset, and both pulses before and after the current successful detection pulse are successfully detected, then the current successful detection pulse is considered a high-risk trap pulse, and high-risk trap pulse information is constructed. Based on the proportion of high-risk trap pulses among all successful detection pulses, combined with the detection rate difference, the trap bit proportion is evaluated using a composite weighted assessment to determine the high-risk trap proportion.

[0102] A classical channel-synchronized atomic clock timing reference can be a time reference used to calibrate the atomic clock timing systems of both communicating parties through a classical communication channel (non-quantum channel).

[0103] Aligned pulse timestamp datasets can be standardized datasets formed by aligning the pulse timestamp data recorded by the sender and receiver based on a synchronized atomic clock reference.

[0104] The time interval distribution dataset can be the set of interval values ​​and their distribution characteristics formed by the time intervals (in nanoseconds) between all adjacent successful detection pulses in the statistically aligned dataset.

[0105] The standard deviation of the historical average time interval can be used as a quantification of the volatility of the pulse time interval within the historical negotiation period.

[0106] An abnormal interval can be an interval in the time interval distribution that exceeds three times the standard deviation of the historical average time interval, representing an abnormal period in which an attacker may forge pulses or interfere with the channel.

[0107] Anomaly interval distribution dataset can be a collection of data containing all anomaly interval distribution locations within the current negotiation timeline.

[0108] High-risk trap pulses can be isolated pulses located within an abnormal range, where neither of the preceding nor following pulses has been successfully detected. They exhibit typical characteristics of decoy pulses injected by the attacker.

[0109] The trap bit percentage can be the percentage of trap bits in all current pulse signals.

[0110] Composite weighted evaluation can be a process of quantifying the scale of the corresponding trap bit proportion by weighting and fusing the proportion of high-risk trap pulses among all successful detection pulses and the difference in detection rate.

[0111] Specifically, in the detection of trap bits, the characteristics of the attacker's trap bits are concealed, making detection difficult. The attacker precisely controls the transmission timing of the interference pulses, making them indistinguishable from legitimate pulses in terms of intensity characteristics. This cannot be detected by basis vector comparison or intensity statistics alone; it requires analysis of microscopic anomalies in the pulse arrival time to identify the trap bits disguised as legitimate pulses. By transmitting a reference time signal through a classical channel, the atomic clocks of the sender and receiver are synchronized at the microsecond level to eliminate clock deviations between devices. The pulse transmission timestamp recorded by the sender and the detection timestamp recorded by the receiver are remapped along the synchronized time axis to generate aligned pulse times. The dataset is tagged, and the time interval between all adjacent successful detection pulses in the aligned dataset is calculated (e.g., the arrival time difference between pulse n and n+1). Based on historical communication data, the average (μ) and standard deviation (σ) of normal time intervals are calculated. The time intervals corresponding to interval values ​​greater than μ+3σ are marked as abnormal intervals. All successful detection pulses located in abnormal intervals are traversed, and the detection status of their preceding and following pulses is checked. If the preceding and following pulses of the current pulse are not successfully detected (i.e., isolated pulses), they are marked as high-risk trap pulses. The proportion of high-risk trap pulses to the total number of successful detection pulses is counted as the high-risk trap percentage.

[0112] This scheme utilizes a timestamp micro-anomaly detection mechanism to identify carefully disguised trap pulses by attackers, overcoming the limitations of traditional strength detection methods, improving the accuracy of trap pulse detection, reducing the amount of invalid key discarded by accurately locating abnormal pulses, improving the utilization rate of surviving bits, and supporting the efficient reuse and splicing of subsequent key fragments.

[0113] In some embodiments, based on the proportion of high-risk traps corresponding to each valid key fragment, a preset trap ratio-compression ratio mapping information is queried to determine the key compression ratio corresponding to each valid key fragment; the proportion of high-risk traps is positively correlated with the corresponding key compression ratio; based on the total length of bit data corresponding to each valid key fragment, a length-scalable hash function is used to perform preliminary homogenization processing on each valid key fragment to determine the key homogenization processing result; based on the key compression ratio corresponding to each valid key fragment, a quantum-resistant hash function is used to perform key compression processing on the key homogenization processing result corresponding to each valid key fragment to determine the compressed dynamic key fragment dataset.

[0114] The preset trap ratio-compression ratio mapping information can be a preset table of correspondence between contamination ratio and compression intensity (e.g., 20% trap → 30% compression).

[0115] The key compression ratio can be the reduction ratio of the key length during the security amplification process.

[0116] A length-scalable hash function can be a hash algorithm with an adjustable output length (such as SHAKE-256) to ensure bit uniformity.

[0117] The result of key homogenization can be intermediate key fragments after scalable hashing, which have statistical randomness.

[0118] Quantum-resistant hash functions can be hash algorithms that resist quantum computing attacks (such as SPHINCS+).

[0119] Specifically, existing fixed-compression-ratio security amplification processing methods are ill-suited to handle the dynamically varying multiple key fragments present in this scheme. This can easily lead to over-compression of some key fragments, reducing usability, or under-compression of others, reducing security. The key compression strategy in this scheme uses the bit trap ratio as a benchmark. A higher bit trap ratio indicates a larger trap bit size in the current bit data, requiring greater key compression strength, and vice versa. Based on this principle, both communicating parties pre-load a trap ratio-compression ratio mapping table (e.g., trap ratio 10% → compression ratio 0.9; ratio 30% → compression ratio 0.9). With a compression ratio of 0.7, this mapping table satisfies the following: the higher the proportion of high-risk traps, the lower the key compression ratio (i.e., the more thorough the compression). For each valid key fragment, a length-scalable hash function (such as SHA-3) is used for processing: Input: variable-length key fragment bitstream, Output: fixed-length homogenized intermediate data (such as a 256-bit digest), eliminating the original fragment length differences and ensuring that subsequent compression inputs are standardized. Then, the above mapping table is queried, and the key compression ratio is determined according to the proportion of high-risk traps in the current fragment. A quantum-resistant hash function is used to compress the homogenized data: a subset of the output digest is truncated according to the compression ratio (such as compression ratio 0.8 → truncating the first 204 bits as the final fragment). After integrating all the compressed fragments, a compressed dynamic key fragment dataset is formed.

[0120] This solution quantifies attack intensity in real time based on the proportion of high-risk traps and dynamically adjusts the compression ratio to precisely match the security amplification strength with the severity of interference. By using layered security amplification processing, it avoids "one-size-fits-all" compression, allowing low-risk fragments to retain more effective bits and high-risk fragments to be compressed more effectively. Compared with traditional fixed compression strategies, it significantly reduces residual security risks in high-interference scenarios. By maximizing the use of low-pollution fragments, it reduces the number of negotiation interruptions triggered by insufficient key length, ensuring that the communication link continues to provide services in interference environments.

[0121] In some embodiments, the key length constraint rule is: the total length of the effective key fragments spliced ​​in multiple rounds does not exceed a preset key length threshold; the negotiation round constraint rule is: according to the service response speed requirements of both communicating parties, a maximum negotiation round is set, and after each round of key fragment multiplexing and splicing processing is completed, the round counter is automatically incremented. When the round counter value is equal to the maximum negotiation round, the currently spliced ​​key fragment is used as the resilient reconstruction key.

[0122] Key length constraint rules can be upper limits on the total bit length of all valid key fragments in a single key concatenation process.

[0123] The preset key length threshold can be the maximum bit length value allowed in a single round of splicing in the key length constraint rules.

[0124] Negotiation round constraint rules can be rules that limit the maximum number of attempts to concatenate key reuse.

[0125] Service response speed requirements can be the requirements of both communicating parties regarding the response time for key negotiation.

[0126] The maximum number of negotiation rounds can be the highest number of rounds allowed for key reuse and splicing (e.g., 3 rounds).

[0127] The round counter can be an accumulator variable that records the number of key concatenation rounds that have been completed.

[0128] Historical fragment cache can be a temporary storage area for data fragments to be spliced ​​together.

[0129] Specifically, during a sustained high-intensity attack, the effective key length obtained each time varies. Allowing unlimited reuse of concatenated key fragments until the key meets the requirements easily leads to low key generation efficiency and high service latency. Therefore, constraints on the number of key negotiation rounds and key length are needed to achieve a good balance between key generation efficiency and key security. Key length constraint rules limit the total length of key concatenation across multiple negotiation rounds. When the key reaches a preset key length threshold, the currently concatenated key is immediately output. Simultaneously, negotiation round constraint rules constrain the maximum number of key negotiation rounds. If the concatenated key cannot reach the preset key length threshold within the corresponding maximum round, the currently concatenated key fragment is used as the resilient reconstruction key to improve key efficiency. Based on service response speed requirements, a maximum negotiation round is set, keeping the maximum negotiation round dynamically changing to prevent attackers from understanding the negotiation pattern. Through key length and negotiation round constraint rules, the efficiency of constructing the final resilient reconstruction key is basically guaranteed, preventing the key negotiation process from falling into an infinite loop. At the same time, uncertainty is introduced into the construction time of the resilient reconstruction key, further improving its security.

[0130] This scheme utilizes key length constraint rules and negotiation round constraint rules to constrain the length and negotiation rounds of the resilient reconstruction key obtained by splicing key fragments, thereby achieving a good balance between key generation efficiency and key security. This ensures the basic efficiency of the final resilient reconstruction key construction, avoids the key negotiation process from falling into an infinite loop, and introduces uncertainty into the construction time of the resilient reconstruction key, further improving the security of the resilient reconstruction key.

[0131] In some embodiments, the key fragment lifecycle management rules are as follows: after each valid key fragment is generated, a lifecycle timer is created and started for it; if a valid key fragment is not used within a preset expiration period, the corresponding valid key is automatically discarded; interruption recovery rules are as follows: when communication between the two parties is interrupted due to interference from the attacker, the number of splicing rounds and the key length are recorded, and key reuse splicing is continued from the nearest valid checkpoint after the link is restored.

[0132] A lifecycle timer can be a countdown timer bound to a single key fragment, starting when the fragment is generated.

[0133] The preset expiration time can be the maximum time threshold for the key fragment to exist (e.g., 60 seconds).

[0134] A valid checkpoint can be a data snapshot that records the progress of key splicing (such as the number of rounds completed or the length of the spliced ​​key).

[0135] Specifically, the lifecycle management of key fragments directly affects key security. If the lifecycle of key fragments is not tracked and constrained, attackers can easily exploit the time difference window of the lifecycle to launch correlation analysis attacks against key fragments. After the valid key fragments undergo layered security amplification processing, a dedicated lifecycle timer is automatically created and started for each valid key fragment via QKMS (Quantum Key Management System). The initial value is set to a preset expiration time. The timer counts down independently. If the fragment is used for splicing within the time limit, the timer is immediately destroyed. If the timer reaches zero (i.e., it expires without being used), automatic discard is triggered: a secure erasure algorithm is called to overwrite the fragment's storage area and release the memory and index resources occupied by the fragment. When the quantum receiver detects a communication interruption event (e.g., no photon response for 1 second): the current splicing process is immediately frozen; the completed splicing rounds (e.g., round counter value) and the length of the spliced ​​key are written to an encrypted valid checkpoint file; when the quantum channel recovers (e.g., photon detection returns to normal): the session layer automatically retrieves the latest valid checkpoint, restores the splicing state based on the checkpoint data (e.g., continuing from round 2, with 3000 bits remaining to be spliced), loads the associated key fragments, and continues to perform multiplexing splicing.

[0136] This solution utilizes key fragment lifecycle management rules to constrain the lifecycle of valid key fragments, thereby preventing attackers from launching correlation analysis attacks against key fragments by exploiting the lifecycle time difference window. At the same time, it uses interruption recovery rules to reduce the key generation time after communication interruption, ensuring that the key generation service maintains high availability under high-intensity continuous interference.

Claims

1. A data quality analysis method for quantum communication data transmission, characterized in that, include: Obtain the real-time key negotiation dataset, analyze the real-time key negotiation dataset, and determine the real-time negotiation bit error rate; The real-time negotiation bit error rate is compared with the protocol bit error rate security threshold. Based on the comparison result, it is determined whether the interference-driven key resilience reconstruction mechanism needs to be activated. If the interference-driven key resilience reconstruction mechanism needs to be activated, then according to the interference-driven key resilience reconstruction mechanism, trap filtering and key fragment multiplexing splicing processing are performed on the surviving bits in several key negotiation processes to determine and output the resilience reconstruction key.

2. The method according to claim 1, characterized in that, The analysis of the real-time key negotiation dataset to determine the real-time negotiation error rate includes: The real-time key negotiation dataset includes a unified index dataset, a sender basis vector sequence, a receiver basis vector sequence, and a negotiation sampling quantity; Based on the unified index dataset, basis vector consistency matching analysis is performed on the sender basis vector sequence and the receiver basis vector sequence, and the corresponding indexes under the basis vector consistency case are recorded to construct a basis vector consistency index set; Based on the negotiated sampling quantity, a corresponding number of indexes are randomly sampled from the basis vector consistency index set to determine the sampling index set; Based on the sampling index set, the number of erroneous bits is determined by publicly comparing the bit values ​​corresponding to each index in the sampling index set through a preset classic authentication channel. The ratio of the number of erroneous bits to the number of negotiated samples is used as the real-time negotiation bit error rate.

3. The method according to claim 2, characterized in that, The step of comparing the real-time negotiated bit error rate with the protocol bit error rate security threshold, and determining whether to activate the interference-driven key resilience reconstruction mechanism based on the comparison result, includes: The protocol error rate security threshold is the protocol security threshold corresponding to the QBER (Quantum Bit Error Rate) value specified in the quantum key distribution protocol currently used by both communicating parties; The real-time negotiation bit error rate is compared with the protocol bit error rate security threshold. If the real-time negotiation bit error rate is less than the protocol bit error rate security threshold, the classic QKD mechanism (Quantum Key Distribution) is adopted. If the real-time negotiation bit error rate is greater than the protocol bit error rate security threshold, then the interference-driven key resilience reconstruction mechanism is activated.

4. The method according to claim 2, characterized in that, The interference-driven key resilience reconstruction mechanism includes: Based on the sampling index set, several basis vectors corresponding to the sampling index set are removed from the sender basis vector sequence and the receiver basis vector sequence to determine the pre-screened basis vector set; Analyze the pre-screened basis set, and filter the bit data in the sender basis sequence and the receiver basis sequence that have the same basis and the same bit value to form a real-time surviving bit dataset; Based on the quantum bit trap detection strategy, the real-time surviving bit dataset is subjected to bit trap filtering processing to determine the dynamic effective key fragment dataset and the bit trap ratio distribution information set; Based on the trap ratio distribution information set and the bit trap ratio distribution information set, according to the bit trap ratio corresponding to each valid key fragment in the valid key fragment dataset, a hierarchical security amplification strategy is executed to determine the compressed dynamic key fragment dataset. Based on the limited reuse strategy, several key fragments are reused and spliced ​​according to the compressed dynamic key fragment dataset to generate the resilient reconstruction key.

5. The method according to claim 4, characterized in that, The quantum bit trap detection strategy includes: Based on the decoy state injection strategy, according to the real-time negotiated bit error rate, the proportion of dynamic pulses that the decoy state pulses need to be in the total transmitted pulses is determined, and according to the proportion of dynamic pulses, the corresponding proportion of the decoy state pulses is generated to construct a decoy state pulse dataset. Based on the decoy state pulse dataset, the precise arrival timestamps of all successfully detected pulses are counted to construct a pulse timestamp distribution dataset; Based on the decoy state pulse dataset, the difference in detection rate between the theoretical detection rate and the actual detection rate of the decoy state pulse is quantified; Based on the timestamp correlation analysis strategy, the pulse timestamp distribution dataset is analyzed according to the detection rate difference to determine the high-risk trap pulse information and the proportion of high-risk traps in the current negotiation process; Based on the high-risk trap pulse information, the bit data under the corresponding index in the real-time surviving bit data set is removed, and the remaining bit data is used as the valid key fragment for the current negotiation process; By integrating the effective key fragments and the proportion of high-risk traps from each negotiation process, the dynamic effective key fragment dataset and the bit trap proportion distribution information set are constructed respectively.

6. The method according to claim 5, characterized in that, The deceptive injection strategy includes: Two types of pulses with varying light intensity levels are defined: signal state pulses and decoy state pulses. The intensity of the signal state pulse is greater than the intensity of the decoy state pulse; Both the signal state pulse and the decoy state pulse are emitted through the same laser pulse emitter; The sum of the intensity of the signal state pulse and the intensity of the decoy state pulse is less than the maximum allowable power of the laser pulse emitter; During the transmission of the signal state pulse and the decoy state pulse, a pulse scheduling strategy based on chaotic sequences is adopted to ensure that the transmission order of the signal state pulse and the decoy state pulse satisfies an aperiodic pseudo-random distribution in the time domain, thereby preventing attackers from inferring the pulse type through time sequence patterns. The ratio of the real-time negotiated bit error rate to the protocol bit error rate security threshold is used as the bit error rate excess ratio. Based on the bit error rate excess ratio, the proportion of the decoy state pulse in the total pulse is linearly increased to determine the dynamic pulse proportion.

7. The method according to claim 6, characterized in that, The timestamp association analysis strategy includes: Based on the classic channel-synchronized atomic clock timing reference, the timestamp data in the pulse timestamp distribution dataset is uniformly aligned to determine the aligned pulse timestamp dataset. Based on the aligned pulse timestamp dataset, the time intervals corresponding to all adjacent successful detection pulses are counted to construct a time interval distribution dataset; Analyze the time interval distribution dataset, define the time intervals within the time interval distribution dataset that are greater than 3 times the standard deviation of the historical average time interval as abnormal intervals, and construct an abnormal interval distribution dataset; If the successful detection pulse is located within any of the abnormal intervals in the abnormal interval distribution dataset, and both pulses before and after the current successful detection pulse are successfully detected, then the current successful detection pulse is taken as a high-risk trap pulse, and the high-risk trap pulse information is constructed. Based on the proportion of high-risk trap pulses among all successful detection pulses, and combined with the detection rate difference, a composite weighted evaluation of the trap bit proportion is performed to determine the proportion of high-risk traps.

8. The method according to claim 7, characterized in that, The layered security amplification strategy includes: Based on the proportion of high-risk traps corresponding to each valid key fragment, query the preset trap ratio-compression ratio mapping information to determine the key compression ratio corresponding to each valid key fragment; The proportion of high-risk traps is positively correlated with the corresponding key compression ratio; Based on the total length of bit data corresponding to each valid key fragment, a length-expandable hash function is used to perform preliminary homogenization processing on each valid key fragment to determine the key homogenization processing result. Based on the key compression ratio corresponding to each valid key fragment, a quantum-resistant hash function is used to perform key compression processing on the key homogenization processing result corresponding to each valid key fragment, thereby determining the compressed dynamic key fragment dataset.

9. The method according to claim 8, characterized in that, The limited reuse strategy includes: Key length constraint rule: The total length of the effective key fragments spliced ​​together in multiple rounds shall not exceed a preset key length threshold; Negotiation round constraint rules: Based on the service response speed requirements of both communicating parties, a maximum number of negotiation rounds is set. After each round of key fragment multiplexing and splicing processing is completed, the round counter is automatically incremented. When the round counter value is equal to the maximum number of negotiation rounds, the currently spliced ​​key fragment is used as the resilient reconstruction key.

10. The method according to claim 9, characterized in that, The method further includes: Key fragment lifecycle management rules: After each valid key fragment is generated, a lifecycle timer is created and started for it; If the valid key fragment is not used within the preset expiration period, the corresponding valid key will be automatically discarded. Interruption recovery rules: When communication between the two parties is interrupted due to interference from the attacker, the number of splicing rounds and the key length that have been completed are recorded. After the link is restored, the key reuse splicing is continued from the nearest valid checkpoint.

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