Data transmission security encryption system of quantum encryption switch

Abstract

The application relates to the technical field of quantum encryption communication, and discloses a data transmission security encryption system of a quantum encryption switch. A quantum channel characteristic acquisition module of the system acquires channel attenuation parameters and noise interference parameters of a quantum channel in real time; a quantum behavior prediction module generates quantum key distribution strategy parameters and quantum state modulation parameter ranges according to the parameters; a quantum state sequence generation module generates an optimized basic quantum state sequence by adopting quantum state compression coding technology in combination with real-time data transmission throughput requirements and channel load states; a quantum key stream adjustment module determines a key stream updating direction and an updating proportion coefficient, and recombines the basic quantum state sequence; and an entanglement phase synchronization module corrects an entanglement phase offset, so that the quantum key generation rate and the data transmission rate are dynamically matched. The system can improve the security, efficiency and stability of data transmission of the quantum encryption switch, and meets the high-security-level data transmission requirements.

Description

Technical Field

[0001] This invention relates to the field of quantum encrypted communication technology, specifically to a data transmission security encryption system for a quantum encrypted switch. Background Technology

[0002] With the rapid development of information technology, the demand for data transmission security is increasing. Quantum encrypted communication, with its unique properties of quantum mechanics, has become an important direction for ensuring high-security data transmission. Among them, the quantum encrypted switch, as a key device in the quantum communication network, undertakes the core tasks of data forwarding and encryption processing. Its data transmission security encryption capability directly determines the security performance of the entire quantum communication network.

[0003] In current quantum-encrypted data transmission processes, the stability of the quantum channel has a crucial impact on the encryption effect. However, existing technologies often lack real-time acquisition of quantum channel characteristics, mostly employing timed or periodic acquisition methods, which cannot promptly obtain dynamic changes in channel attenuation parameters and noise interference parameters. When the quantum channel experiences sudden attenuation or increased noise interference, the delayed channel characteristic data will prevent subsequent quantum key distribution strategies and quantum state modulation parameters from being adjusted in a timely manner, thus affecting the quality of quantum key generation and the security of data transmission.

[0004] Existing quantum encryption systems typically consider only the inherent characteristics of the quantum states when generating quantum state sequences, neglecting real-time data transmission throughput requirements and channel load conditions. When data transmission throughput suddenly increases or channel load is high, traditional quantum state sequence generation methods struggle to adapt quickly, easily leading to quantum state sequence transmission congestion or resource waste, thus reducing data transmission efficiency. Furthermore, in the quantum key stream adjustment stage, existing technologies mostly rely on fixed adjustment rules, lacking a scientific basis for determining the key stream update direction and update ratio coefficients. This results in limited security improvements after adjustment of the quantum state sequence, making it difficult to cope with complex and ever-changing network attack risks.

[0005] Entangled phase synchronization of quantum states is crucial for ensuring that the quantum key generation rate matches the data transmission rate. Existing systems often lack a precise correction mechanism based on the range of quantum state modulation parameters when dealing with entangled phase shifts. When a shift occurs, it cannot be corrected promptly and accurately, easily leading to a mismatch between the quantum key generation rate and the data transmission rate. This can result in either key redundancy leading to resource waste or insufficient keys affecting the continuity of data transmission, further restricting the overall performance of quantum encryption switches in data transmission. Summary of the Invention

[0006] The purpose of this invention is to provide a secure encryption system for data transmission of a quantum encryption switch, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides a data transmission security encryption system for a quantum encryption switch, the system comprising:

[0008] The quantum channel characteristic acquisition module is used to acquire the channel attenuation parameters and noise interference parameters of the quantum channel in real time.

[0009] The quantum behavior prediction module is used to generate quantum key distribution strategy parameters and quantum state modulation parameter ranges based on the quantum channel characteristic parameters using a quantum behavior prediction algorithm;

[0010] The quantum state sequence generation module is used to generate an optimized basic quantum state sequence based on the real-time throughput requirements of data transmission and the channel load status, using quantum state compression coding technology.

[0011] The quantum key stream adjustment module is used to determine the key stream update direction and update ratio coefficient according to the quantum key distribution strategy parameters, and to recombine the optimized basic quantum state sequence to generate a quantum state sequence with adjusted key stream.

[0012] The entangled phase synchronization module is used to correct the entangled phase offset of the quantum state sequence after the key stream is adjusted by utilizing the range of quantum state modulation parameters, thereby achieving dynamic matching between the quantum key generation rate and the data transmission rate.

[0013] Preferably, the quantum behavior prediction module includes:

[0014] A quantum channel modeling unit is used to construct a dynamic correlation model between the quantum bit error rate and the channel capacity based on the channel attenuation parameters and noise interference parameters.

[0015] The strategy parameter generation unit is used to calculate the key update threshold range based on the dynamic correlation model within a preset prediction period, and to define the upper limit of amplitude, lower limit of phase, and step size constraints of quantum state modulation parameters.

[0016] The parameter sequence optimization unit is used to generate a candidate modulation parameter sequence based on the key update threshold range and optimization target using a quantum behavior prediction algorithm.

[0017] The continuity verification unit is used to perform parameter mutation constraint verification on the candidate modulation parameter sequence to generate a target modulation parameter combination that meets the temporal continuity requirements.

[0018] Preferably, the parameter sequence optimization unit includes:

[0019] The threshold interval division sub-unit is used to divide the key update threshold interval into multiple error-sensitive sub-intervals based on the numerical distribution characteristics of the quantum bit error rate.

[0020] An initial parameter set generation subunit is used to generate an initial modulation parameter set corresponding to each error-sensitive sub-interval based on the upper limit of amplitude and the lower limit of phase.

[0021] The parameter discretization processing subunit is used to perform discretization segmentation processing on the expanded modulation parameter set according to the step size constraint.

[0022] The sequence generation subunit is used to select modulation parameters that meet the multi-stage key security requirements and generate a candidate modulation parameter sequence within the preset prediction period.

[0023] Preferably, the quantum state sequence generation module includes:

[0024] A reference waveform generation unit is used to set the initial pulse width and entanglement interval of the basic quantum state sequence according to the real-time throughput requirements.

[0025] A load adjustment unit is used to calculate the width compensation amount for each quantum state unit based on the channel load state.

[0026] A sequence recombination unit is used to superimpose the width compensation amount with the initial pulse width to generate a transition quantum state sequence;

[0027] An interval smoothing unit is used to eliminate abrupt changes in the interval between adjacent quantum state units in the transition quantum state sequence.

[0028] Preferably, the quantum key stream adjustment module includes:

[0029] The parameter parsing unit is used to take the absolute value of the numerical change of the quantum key distribution strategy parameters as the update ratio coefficient, and determine the key stream update direction according to a preset threshold.

[0030] A duration correction unit is used to establish a high-level duration correction rule for each quantum state unit in the optimized basic quantum state sequence;

[0031] The mutation verification unit is used to perform high-level duration mutation threshold verification on the corrected quantum state unit;

[0032] The smooth recombination unit is used to perform smooth recombination processing on units that exceed a preset mutation threshold.

[0033] Preferably, the entangled phase synchronization module includes:

[0034] A modulation feature extraction unit is used to identify the rising and falling time points of quantum state amplitude changes within the range of quantum state modulation parameters.

[0035] A phase offset calculation unit is used to calculate the entanglement phase correction amount of each quantum state unit based on the rising edge time point and the falling edge time point;

[0036] A timing calibration unit is used to superimpose the entangled phase correction amount with the initial triggering time point of the quantum state unit to generate a calibration quantum state sequence;

[0037] The timing conflict resolution unit is used to perform minimum interval constraint verification on the trigger time interval of adjacent calibration quantum state units.

[0038] Preferably, the phase offset calculation unit includes:

[0039] The change calculation subunit is used to extract the absolute value of the quantum state amplitude change corresponding to the rising edge time point and the falling edge time point;

[0040] A correction coefficient generation subunit is used to define a phase correction coefficient based on the absolute value of the quantum state amplitude change.

[0041] The boundary constraint processing subunit is used to perform timing boundary constraint processing on the initial phase correction amount.

[0042] Preferably, the system further includes:

[0043] The transmission security assessment module is used to monitor the bit error rate offset and channel capacity fluctuation in real time during quantum key distribution.

[0044] The security policy correction module is used to generate quantum state modulation parameter correction instructions based on the quantum bit error rate offset and channel capacity fluctuation.

[0045] The parameter closed-loop update module is used to feed back the quantum state modulation parameter correction instruction to the quantum behavior prediction module to update the quantum state modulation parameter range.

[0046] Preferably, the security policy correction module includes:

[0047] An anomaly analysis unit is used to perform joint normalization processing on the bit error rate offset and channel capacity fluctuation of the qubit;

[0048] A secondary encryption decision unit is used to generate quantum state remodulation trigger coefficients based on the standardized processing results;

[0049] The instruction generation unit is used to generate a quantum state modulation parameter correction instruction when the quantum state remodulation trigger coefficient exceeds a preset threshold.

[0050] Preferably, the secondary encryption decision unit includes:

[0051] The transmission feature extraction subunit is used to calculate the quantum key verification failure rate and data packet retransmission rate;

[0052] The decision model processing subunit is used to process the quantum key verification failure rate and data packet retransmission rate through the principal component discrimination model.

[0053] The threshold comparison subunit is used to compare the output of the principal component discrimination model with a preset security threshold to generate quantum state remodulation trigger coefficients.

[0054] Compared with the prior art, the beneficial effects of the present invention are:

[0055] This quantum-encrypted switch's data transmission security encryption system, through the inclusion of a quantum channel characteristic acquisition module, can acquire channel attenuation and noise interference parameters of the quantum channel in real time. This overcomes the limitations of traditional timed or periodic acquisition methods, dynamically capturing instantaneous changes in quantum channel characteristics. This provides a precise data foundation for subsequent processing steps based on channel characteristic parameters. Based on the real-time acquired channel characteristic parameters, the quantum behavior prediction module uses a quantum behavior prediction algorithm to generate quantum key distribution strategy parameters and quantum state modulation parameter ranges. This ensures that the quantum key distribution strategy closely follows channel state adjustments, avoiding key distribution strategy lag caused by changes in channel characteristics. Simultaneously, a reasonable quantum state modulation parameter range provides scientific guidance for subsequent quantum state optimization processing.

[0056] The quantum state sequence generation module, based on the real-time throughput requirements of data transmission and the channel load status, employs quantum state compression coding technology to generate optimized basic quantum state sequences. This overcomes the shortcomings of traditional quantum state sequence generation processes that ignore transmission requirements and channel load. When data transmission throughput is high or the channel load is heavy, quantum state compression coding technology can improve the transmission efficiency of quantum state sequences and reduce transmission congestion while ensuring quantum state security. Conversely, when throughput is low or the channel load is light, it can also avoid unnecessary waste of quantum state resources and achieve rational allocation of these resources.

[0057] The quantum keystream adjustment module determines the keystream update direction and update ratio coefficient based on the quantum key distribution strategy parameters, and reassembles the optimized basic quantum state sequence to generate a quantum state sequence with adjusted keystream. This reassembly method does not rely on fixed rules, but rather combines the actual key distribution strategy requirements, making the adjusted quantum state sequence more in line with the current data transmission security requirements, enhancing the quantum state sequence's resistance to attacks, and further improving the encryption security during data transmission.

[0058] The entangled phase synchronization module utilizes the range of quantum state modulation parameters to correct the entangled phase offset of the quantum state sequence after key stream adjustment, accurately addressing the offset problem that occurs during quantum state entanglement phase transmission. By correcting the offset in real time, it ensures that the quantum key generation rate can dynamically adapt to changes in the data transmission rate. When the data transmission rate increases, the quantum key generation rate can be adjusted accordingly to meet encryption requirements; when the data transmission rate decreases, the quantum key generation rate can also be adjusted accordingly, avoiding redundancy of key resources. This achieves efficient coordination between quantum key generation and data transmission, improving the stability and reliability of data transmission in the entire quantum encryption switch. Attached Figure Description

[0059] Figure 1 This is a timing diagram of a data transmission security encryption system for a quantum encryption switch according to the present invention;

[0060] Figure 2 This is a schematic diagram of the working principle of the quantum behavior prediction module;

[0061] Figure 3 A schematic diagram of the working principle of the quantum state sequence generation module;

[0062] Figure 4 This is a schematic diagram illustrating the working principle of the entanglement phase synchronization module. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] Please see Figure 1 This invention provides a data transmission security encryption system for a quantum encryption switch, the system comprising:

[0065] The system achieves dynamic adaptive matching between quantum key distribution and data transmission through multi-module collaboration. First, a quantum channel characteristic acquisition module acquires channel attenuation and noise interference parameters of the quantum channel in real time. Based on these parameters, a quantum behavior prediction module uses a quantum behavior prediction algorithm to generate quantum key distribution strategy parameters and the range of quantum state modulation parameters. A quantum state sequence generation module generates an optimized basic quantum state sequence using quantum state compression coding technology, based on the real-time throughput requirements of data transmission and the channel load state. A quantum key stream adjustment module reassembles the basic quantum state sequence according to the key stream update direction and update ratio determined by the quantum key distribution strategy parameters, generating an adjusted quantum state sequence. An entanglement phase synchronization module then uses the quantum state modulation parameter range to correct the entanglement phase offset of the adjusted sequence, ultimately achieving dynamic matching between the quantum key generation rate and the data transmission rate.

[0066] Example 1: See Figure 2 In the actual operation of the quantum encryption switch, the dynamic working process of the quantum behavior prediction module constitutes the core of the system's adaptive capability. This module continuously receives real-time data streams from the quantum channel characteristic acquisition module. These data include continuous sampling values ​​of the quantum channel's channel attenuation parameters and noise interference parameters. The channel attenuation parameter reflects the energy loss during photon transmission, while the noise interference parameter quantifies the degree to which the environment disrupts the superposition and entanglement properties of quantum states. These parameters together depict the current physical transmission characteristics of the channel.

[0067] The quantum channel modeling unit first preprocesses the raw data, including filtering, denoising, and outlier removal, to eliminate potential transient interference during measurements. Based on the processed data, this unit constructs a dynamic correlation model. The core of this model lies in establishing a mathematical mapping relationship between the qubit error rate (BER) and the channel capacity. This relationship is not static but adjusts in real-time as channel conditions fluctuate. The model comprehensively considers the signal strength reduction caused by attenuation and the probability of random phase flips introduced by noise, calculating the highest BER level that can be tolerated to maintain reliable quantum key distribution under current channel conditions, as well as the maximum theoretical key capacity that the channel can support. This dynamic model provides a quantitative theoretical basis for all subsequent decisions.

[0068] The strategy parameter generation unit operates based on the output of this dynamic correlation model. Within a pre-defined prediction period—which can be dynamically configured according to network stability—it performs forward-looking calculations. This unit first calculates the key update threshold range, a dynamically changing numerical range. Its lower limit is determined by the minimum security level required by the current service, while its upper limit is limited by the maximum feasible value given by the channel capacity model. Simultaneously, this unit defines a set of boundary constraints for quantum state modulation parameters: the upper limit of amplitude is jointly determined by the maximum secure output power of the laser at the transmitter and channel attenuation, preventing excessively strong signals from causing nonlinear effects or security problems; the lower limit of phase is determined based on the channel coherence time, avoiding excessively rapid phase changes that could lead to indistinguishable quantum states; and the step size constraint limits the maximum magnitude of parameter adjustments between adjacent prediction periods, ensuring the stability of system evolution.

[0069] After receiving these boundary constraints, the parameter sequence optimization unit begins generating specific candidate parameter sequences. Its internal threshold interval partitioning subunit first finely divides the key update threshold interval. The partitioning is based on the sensitivity of the bit error rate to key security; typically, low-error-rate regions are partitioned more sparsely, while high-error-rate regions are partitioned more densely, because even small changes in parameters in high-error-rate regions can lead to a sharp decrease in security. The initial parameter set generation subunit generates a corresponding initial modulation parameter set for each error-sensitive sub-interval. This is achieved by using methods such as uniform sampling or Latin hypercube sampling within the feasible region defined by the upper amplitude limit and lower phase limit to generate a batch of discrete parameter combination points. The parameter discretization processing subunit further processes these initial parameter points according to the step size constraint, ensuring that the change amplitude between any two adjacent parameter points is within the allowable range of the step size constraint, forming discrete parameter options that meet the adjustment granularity requirements. Finally, the sequence generation subunit is responsible for selecting and concatenating a complete candidate modulation parameter sequence from these discrete parameter options over the entire prediction period's time axis. The selection criteria are to ensure that the entire sequence meets the security requirements at each time point while minimizing unnecessary parameter jumps, thus achieving a balance between security and stability.

[0070] The continuity verification unit, as the final quality control step, performs a temporal smoothness check on the generated candidate modulation parameter sequence. It checks whether the changes between each parameter point and its preceding and following points exceed the range specified by the step size constraint. For parameter jump points exceeding the allowable variation range, this unit initiates an interpolation smoothing algorithm to insert one or more transition parameter values ​​between the jump points, making the changes in the entire parameter sequence smoother and preventing unstable or unpredictable behavior of the quantum state preparation device due to abrupt parameter settings. Finally, this unit outputs a target modulation parameter combination that meets both safety requirements and operational feasibility. This combination will be sent to the subsequent quantum state sequence generation module and entangled phase synchronization module as guiding parameters for their operation.

[0071] The entire quantum behavior prediction module operates as an iterative process. It continuously receives the latest channel characteristic data, re-evaluates the channel model, updates the prediction parameters, and outputs new combinations of target modulation parameters. This enables the entire encryption system to continuously adapt to the ever-changing quantum channel environment and maintain secure and efficient key distribution.

[0072] Example 2: See Figure 3 During the operation of the quantum encryption switch, the quantum state sequence generation module and the quantum key stream adjustment module work together to transform the abstract policy parameters from the upstream into specific quantum state sequences that can drive physical devices and enable them to dynamically respond to key update commands.

[0073] The quantum state sequence generation module starts working first. Its reference waveform generation unit receives the real-time throughput requirements for data transmission, typically given as a target bit rate. This unit interprets this macroscopic requirement into microscopic quantum state sequence parameters. Based on the system's core clock frequency, it calculates the theoretical time slot length for each quantum state unit, using this as the initial pulse width. Simultaneously, it sets a basic entanglement interval based on the minimum distinguishable time interval between quantum states and the system synchronization accuracy, ensuring that adjacent quantum states do not confuse during transmission and detection. The load adjustment unit synchronously monitors the channel load status. Channel load is a dynamically changing indicator, reflecting the proportion of current data traffic to the total capacity of the channel. This unit calculates a dynamic width compensation amount based on this proportion. The calculation logic is that when the channel load is high, competition intensifies, requiring a slight increase in the pulse width of individual quantum state units to enhance their anti-interference capability and distinguishability; conversely, when the load is light, the pulse width can be appropriately shortened to improve the overall efficiency of the sequence. The sequence reassembly unit superimposes the initial pulse width with the real-time calculated width compensation amount unit by unit. This superposition process is not a simple addition, but a fusion based on a predefined weighting function to generate a transition quantum state sequence. The pulse width and interval of this transition sequence already incorporate throughput requirements and real-time load information, but its timing characteristics may still be coarse. An interval smoothing unit then processes the transition sequence. It scans the time intervals between all adjacent quantum state units in the sequence, identifying interval points where changes are too abrupt. For these points, it uses digital filtering or interpolation algorithms to smooth the transition curves of the intervals, eliminating sequence jitter caused by instantaneous load fluctuations, and ultimately outputting a time-stable, parameter-optimized fundamental quantum state sequence.

[0074] The optimized basic quantum state sequence is then fed into the quantum key stream adjustment module, whose core task is to execute the key update strategy from the quantum behavior prediction module. The update parameter parsing unit receives the quantum key distribution strategy parameters, a comprehensive instruction. This unit parses the instruction, extracting two key pieces of information: the update direction and the update scaling factor. The update direction indicates whether the adjustment enhances security (usually meaning increasing sequence complexity or randomness) or improves transmission efficiency. The update scaling factor is a quantized value; its absolute value represents the magnitude of the adjustment, typically derived directly from the numerical change in the strategy parameters. The duration correction unit, based on the parsed instruction, substantially modifies each unit of the basic quantum state sequence. Its core operation is correcting the high-level duration of each quantum state unit. The correction rule calculates the unit's initial duration using the update scaling factor. If the update direction is to enhance security, the high-level time of critical units may be extended to embed more verification information; if it's to improve efficiency, the duration may be shortened. The entire correction process is strictly controlled, ensuring that the corrected duration remains within the physical limits of the quantum state preparation and detection equipment.

[0075] The mutation check unit then scans the entire corrected sequence to identify timing abrupt changes caused by drastic parameter adjustments. It calculates the relative rate of change of the high-level duration of each unit in the sequence with respect to its preceding unit and compares this rate to a preset mutation threshold based on system stability. Units with rates exceeding the threshold are marked as "mutation points." The smoothing and recombination unit ultimately processes these mutation points. It optimizes the recombination of local sequence segments containing mutation points by introducing a smoothing function (such as a linear ramp or sigmoid function) to create a gentle parameter transition band before and after the mutation point. This replaces a drastic jump with several subtle changes, ensuring that the output, keystream-adjusted quantum state sequence both adheres to the key update strategy and maintains temporal smoothness and stability, enabling reliable execution by the backend physical devices.

[0076] The entire process starts with abstract requirements, goes through a series of progressively refined data transformations and processing, and finally generates a physical control signal that meets communication requirements, complies with security policies, and is engineering-feasible, demonstrating the system's efficient bridging capability from the digital domain to the physical domain.

[0077] Example 3: See Figure 4In the operation of a quantum cryptographic switch, the entanglement phase synchronization module is responsible for the final timing fine-tuning of the quantum state sequence that has been processed by the quantum key stream adjustment module. Its core task is to correct the entanglement phase offset of each quantum state unit in the sequence to achieve a precise dynamic match between the quantum key generation rate and the data transmission rate. This module receives two key inputs: first, the range of quantum state modulation parameters from the quantum behavior prediction module, which defines the boundaries and trends of phase adjustment; and second, the quantum state sequence after key stream adjustment from the previous module, which already contains pulse width and basic timing information.

[0078] The modulation feature extraction unit within the module begins operation first. This unit performs in-depth analysis of the quantum state modulation parameter range, with its primary goal being to accurately identify the characteristic time points of the quantum state amplitude changes described within the parameter range, namely the rising edge and falling edge time points. These time points do not exist directly in the data but need to be extracted from the parameter model describing the amplitude change trend using algorithms. Internally, the unit employs edge detection technology from digital signal processing to discretize and analyze the analog waveform whose amplitude changes over time. By calculating the waveform's difference or gradient and setting reasonable thresholds, it locates the start (rising edge) and end (falling edge) moments when significant amplitude changes occur. The set of these time points forms the basis for subsequent phase calculations.

[0079] The phase shift calculation unit begins operation. Its core function is to calculate the required entanglement phase correction for each quantum state unit using the rising and falling edges of the time points. Its internal processing flow consists of three sub-steps. First, the change calculation sub-unit extracts the absolute value of the quantum state amplitude change corresponding to each characteristic time point. This absolute value is obtained by querying the amplitude value of the modulation parameter model at the corresponding time point and calculating its difference from the previous time point; it quantifies the severity of the amplitude change at that time point. Next, the correction coefficient generation sub-unit defines a phase correction coefficient based on these absolute values ​​of amplitude change. This coefficient is a normalized value, calculated based on the logic that the more severe the amplitude change, the greater the potential impact on phase stability, and therefore the greater the required compensation or correction. Finally, the boundary constraint processing sub-unit applies temporal boundary constraints to the initially calculated phase correction. This constraint ensures that the calculated correction does not cause the quantum state's phase value to exceed the range achievable by its physical modulator, nor does it cause excessive phase differences between adjacent units, leading to synchronization failure. The output of this unit is an array containing the phase correction for each quantum state unit.

[0080] The timing calibration unit is the core execution component of the module. It receives two inputs: an array of phase correction values ​​provided by the phase offset calculation unit, and the initial trigger time of each unit in the adjusted quantum state sequence of the keystream. The unit's operation involves converting the phase correction values ​​into actual time offsets and applying them to the initial trigger time. This conversion relationship is described by the following formula:

[0081]

[0082] In this formula, This represents the new triggering time point after the i-th quantum state unit has been calibrated. This indicates the original, uncalibrated trigger time of the unit. Δφ (i) This is the phase correction calculated by the phase offset calculation unit for the i-th unit, in radians. carrier This is the fundamental frequency of the system carrier, a fixed system parameter measured in Hertz. The entire fraction... A linear transformation from the phase domain to the time domain was completed, and the specific amount of time required to advance or delay the trigger moment was calculated. Through unit-by-unit calculation, a completely new sequence of quantum states with calibrated phases was generated for that unit.

[0083] Finally, the timing conflict resolution unit performs a final quality check on the calibrated sequence. Its task is to ensure that the calibration operation has not introduced any new timing problems; that is, the triggering time interval between adjacent quantum state units must be greater than the minimum interval constraint required by the system hardware. This unit scans the entire calibration sequence and calculates... The value is then compared with the system's preset minimum time interval Δt. min Compare. For any condition satisfying Δt... (i) <Δt min For a given pair of units, the conflict resolution algorithm will be activated. A typical approach is to keep the trigger time of the first unit unchanged and adjust the trigger time of the second unit to... The timing of all subsequent units is then fine-tuned accordingly, or the phase correction amount is redistributed within a certain range. After this step, the final quantum state sequence, which satisfies both phase synchronization requirements and hardware timing constraints, is output and sent to subsequent physical layer devices for execution. Through this series of meticulous, model-based calculations and adjustments, the entire entangled phase synchronization module achieves deep integration and coordination between the quantum key generation process and data stream transmission in the time dimension.

[0084] Example 4: In the operational architecture of the quantum encryption switch, the transmission security assessment module, the security policy correction module, and the parameter closed-loop update module together constitute a dynamic security situation awareness and adaptive adjustment closed loop. This system continuously monitors the intrinsic quality of the quantum key distribution process and external channel conditions, and generates refined control instructions accordingly to ensure the robust operation of the encryption system in changing environments.

[0085] The transmission security assessment module, acting as the system's "sensory system," continuously acquires raw data from the quantum receiver and the classical channel monitoring interface. Its core monitoring metrics include qubit error rate (BER) offset and channel capacity fluctuation. The BER offset is not a raw BER value, but a calculated relative quantity. Internally, this module maintains a baseline BER calculated using a sliding window of historical data; the offset is the difference between the current instantaneous BER and this baseline value. This difference effectively filters out slow environmental drift and more sensitively detects abrupt changes in the BER. Similarly, channel capacity fluctuation is also a relative indicator, measuring the deviation of the currently estimated channel capacity from the recent average capacity. This module continuously collects and calculates these two metrics at a fixed sampling period, forming two data streams that change over time, providing a data foundation for subsequent security posture analysis.

[0086] The security policy correction module acts as the "brain," analyzing and making decisions based on this monitoring data. Its internal anomaly analysis unit first performs joint standardization on the continuously arriving bit error rate offset and capacity fluctuation data. This process aims to eliminate analytical bias caused by the different dimensions and orders of magnitude of the two indicators. The process first calculates the mean and standard deviation of each data stream within a time window, then performs Z-score standardization on each new data point, transforming it into a dimensionless value with a mean of zero and a standard deviation of one. After standardization, the two previously incomparable indicators are mapped to the same operable numerical range, as shown in Table 1.

[0087] Table 1: The abnormal indicators after joint standardization are as follows.

[0088]

[0089] This unit combines two standardized values ​​into a weighted composite anomaly index based on preset weighting coefficients. This index is a single, comprehensive measure of security posture. The secondary encryption decision unit then generates a quantum state remodulation trigger coefficient based on this composite anomaly index. The calculation of this coefficient takes into account the historical distribution of the index within a recent time window, for example, comparing it with the historical mean or a certain percentile. The instruction generation unit continuously compares the remodulation trigger coefficient with a preset static threshold in real time. Once the coefficient is found to consistently and significantly exceed the threshold, the current security posture is determined to have deteriorated to the point requiring active intervention, and a quantum state modulation parameter correction instruction is generated. This instruction is not a simple Boolean command, but a structured data body that includes the parameter identifier for the proposed adjustment (such as amplitude or phase), the direction of adjustment (increase or decrease), and a proposed adjustment gradient.

[0090] The parameter closed-loop update module acts as the "neural pathway" for feedback. It receives modulation parameter correction instructions from the security policy correction module and converts them into an input format recognizable and digestible by the quantum behavior prediction module. This module maps the adjustment information contained in the instructions to the boundaries of the quantum state modulation parameter range maintained by the quantum behavior prediction module or the generation rules of the initial parameter set. For example, an instruction to "moderately reduce the amplitude upper limit in the next prediction cycle" is fed back to the policy parameter generation unit of the prediction module. When calculating the amplitude upper limit for the next cycle, this unit selects a more conservative value under the constraint of this instruction. In this way, the downstream module's perception of the security situation is effectively fed back to the upstream prediction and parameter generation stages, thus completing a full closed loop from perception to decision-making to execution at the system level. This enables the entire encryption system to dynamically respond to changes in the internal and external environment.

[0091] Example 5: In the security policy correction module of the quantum encryption switch, the execution process of the secondary encryption decision unit constitutes the refined core of system security situation assessment and response decision-making. The operation of this unit does not rely on a single, directly measured physical layer indicator, but is based on in-depth analysis and fusion judgment of two key derived indicators generated in the interaction of transport layer protocols, thereby generating more robust and accurate quantum state remodulation trigger coefficients.

[0092] The activation of this unit relies on its internal transmission feature extraction subunit. This subunit does not directly manipulate quantum signals but instead listens to and analyzes the classical authentication and data transmission channels tightly coupled with the quantum key distribution process. Its primary task is to calculate the quantum key verification failure rate. This metric is derived by statistically analyzing all quantum key verification transactions occurring within a sliding time window. Specifically, it records the number of times the receiver sends a "key verification failed" message and divides this number by the total number of key verifications within the same window to obtain a ratio. This ratio directly reflects the consistency issues of the currently generated quantum key; its increase often indicates that channel interference or potential eavesdropping is affecting the transmission or measurement of the quantum state. Simultaneously, this subunit calculates the data packet retransmission rate in parallel. This metric is obtained by monitoring the transmission of data packets encrypted with the quantum key in the classical channel. It counts the number of data packets requested for retransmission by the receiver within a specific time period due to checksum errors or timeouts and compares this number with the total number of data packets sent. An unusually high retransmission rate may indicate that, although key verification passes at the protocol level, errors caused by noise or disturbances have accumulated to the point of affecting the integrity of application-layer data. These two rates reveal the state of system transmission reliability from different perspectives.

[0093] The transmission feature extraction subunit packages the calculated key verification failure rate and data packet retransmission rate, aligned with timestamps, and sends them to the decision model processing subunit. The core of this subunit is a pre-trained principal component discriminant model. This model is designed for dimensionality reduction and feature enhancement. It receives raw, potentially correlated failure and retransmission rate data streams and transforms these two dimensions of raw data into a new, orthogonal feature space through its internal principal component analysis projection matrix. In this new space, the first principal component direction represents the most prevalent and variance-rich pattern in the joint variation of failure and retransmission rates, typically reflecting the overall security and health of the system. The second principal component captures the remaining variation information that may be related to specific noise patterns or attack characteristics. The model then uses a linear discriminant function to weight and synthesize the projected principal component feature vectors, ultimately outputting a scalar value, namely the security risk score. This score is a highly condensed indicator that maximizes the separation between "normal" and "abnormal" transmission states; its value directly corresponds to the probability of the system facing overall security risk.

[0094] The threshold comparison subunit is the final decision-making stage. It receives the security risk score output by the principal component discrimination model and compares it with one or more preset security thresholds in real time. These thresholds are not fixed but can be flexibly configured by the system administrator according to different security protection level strategies. For example, in scenarios requiring extremely high security, a lower threshold can be set, making the system sensitive to even small increases in the risk score, thus triggering a response as early as possible. The comparison logic is usually a simple conditional judgment: comparing the current security risk score with the set threshold. The output is processed by a normalization function and mapped to a value between zero and one. This value is the final quantum state remodulation trigger coefficient. The closer this coefficient is to one, the higher the security risk level indicated by the current transmission characteristics, and the more urgent the necessity for the system to initiate quantum state remodulation (i.e., return upstream to adjust modulation parameters).

[0095] Through this multi-layered method based on statistical feature extraction and machine learning model discrimination, the secondary encryption decision unit can extract profound security insights from seemingly messy protocol interaction data, thus providing a scientific and reliable basis for the adaptive adjustment of the entire encryption system in complex environments.

[0096] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0097] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A data transmission security encryption system for a quantum encryption switch, characterized in that, include: The quantum channel characteristic acquisition module is used to acquire the channel attenuation parameters and noise interference parameters of the quantum channel in real time. The quantum behavior prediction module is used to generate quantum key distribution strategy parameters and quantum state modulation parameter ranges based on the quantum channel characteristic parameters using a quantum behavior prediction algorithm; The quantum state sequence generation module is used to generate an optimized basic quantum state sequence based on the real-time throughput requirements of data transmission and the channel load status, using quantum state compression coding technology. The quantum key stream adjustment module is used to determine the key stream update direction and update ratio coefficient according to the quantum key distribution strategy parameters, and to recombine the optimized basic quantum state sequence to generate a quantum state sequence with adjusted key stream. The entangled phase synchronization module is used to correct the entangled phase offset of the quantum state sequence after the key stream is adjusted by utilizing the range of quantum state modulation parameters, so as to achieve dynamic matching between the quantum key generation rate and the data transmission rate. The quantum key stream adjustment module includes: The update parameter parsing unit is used to take the absolute value of the numerical change of the quantum key distribution strategy parameters as the update ratio coefficient and determine the key stream update direction according to a preset threshold; the duration correction unit is used to establish the high-level duration correction rule for each quantum state unit in the optimized basic quantum state sequence; the mutation verification unit is used to perform high-level duration mutation threshold verification on the corrected quantum state units; and the smooth recombination unit is used to perform smooth recombination processing on units that exceed the preset mutation threshold. The entangled phase synchronization module includes: The modulation feature extraction unit is used to identify the rising and falling edge times of the quantum state amplitude change within the range of quantum state modulation parameters; the phase offset calculation unit is used to calculate the entanglement phase correction amount of each quantum state unit based on the rising and falling edge times; the timing calibration unit is used to superimpose the entanglement phase correction amount with the initial trigger time of the quantum state unit to generate a calibration quantum state sequence; and the timing conflict resolution unit is used to perform minimum interval constraint verification on the trigger time interval of adjacent calibration quantum state units.

2. The data transmission security encryption system of the quantum encryption switch according to claim 1, characterized in that, The quantum behavior prediction module includes: A quantum channel modeling unit is used to construct a dynamic correlation model between the quantum bit error rate and the channel capacity based on the channel attenuation parameters and noise interference parameters. The strategy parameter generation unit is used to calculate the key update threshold range based on the dynamic correlation model within a preset prediction period, and to define the upper limit of amplitude, lower limit of phase, and step size constraints of quantum state modulation parameters. The parameter sequence optimization unit is used to generate a candidate modulation parameter sequence based on the key update threshold range and optimization target using a quantum behavior prediction algorithm. The continuity verification unit is used to perform parameter mutation constraint verification on the candidate modulation parameter sequence to generate a target modulation parameter combination that meets the temporal continuity requirements.

3. The data transmission security encryption system of the quantum encryption switch according to claim 2, characterized in that, The parameter sequence optimization unit includes: The threshold interval division sub-unit is used to divide the key update threshold interval into multiple error-sensitive sub-intervals based on the numerical distribution characteristics of the quantum bit error rate. An initial parameter set generation subunit is used to generate an initial modulation parameter set corresponding to each error-sensitive sub-interval based on the upper limit of amplitude and the lower limit of phase. The parameter discretization processing subunit is used to perform discretization segmentation processing on the expanded modulation parameter set according to the step size constraint. The sequence generation subunit is used to select modulation parameters that meet the multi-stage key security requirements and generate a candidate modulation parameter sequence within the preset prediction period.

4. The data transmission security encryption system of the quantum encryption switch according to claim 1, characterized in that, The quantum state sequence generation module includes: A reference waveform generation unit is used to set the initial pulse width and entanglement interval of the basic quantum state sequence according to the real-time throughput requirements. A load adjustment unit is used to calculate the width compensation amount for each quantum state unit based on the channel load state. A sequence recombination unit is used to superimpose the width compensation amount with the initial pulse width to generate a transition quantum state sequence; An interval smoothing unit is used to eliminate abrupt changes in the interval between adjacent quantum state units in the transition quantum state sequence.

5. The data transmission security encryption system of the quantum encryption switch according to claim 1, characterized in that, The phase offset calculation unit includes: The change calculation subunit is used to extract the absolute value of the quantum state amplitude change corresponding to the rising edge time point and the falling edge time point; A correction coefficient generation subunit is used to define a phase correction coefficient based on the absolute value of the quantum state amplitude change. The boundary constraint processing subunit is used to perform timing boundary constraint processing on the initial phase correction amount.

6. The data transmission security encryption system of the quantum encryption switch according to claim 1, characterized in that, Also includes: The transmission security assessment module is used to monitor the bit error rate offset and channel capacity fluctuation in real time during quantum key distribution. The security policy correction module is used to generate quantum state modulation parameter correction instructions based on the quantum bit error rate offset and channel capacity fluctuation. The parameter closed-loop update module is used to feed back the quantum state modulation parameter correction instruction to the quantum behavior prediction module to update the quantum state modulation parameter range.

7. The data transmission security encryption system of the quantum encryption switch according to claim 6, characterized in that, The security policy correction module includes: An anomaly analysis unit is used to perform joint normalization processing on the bit error rate offset and channel capacity fluctuation of the qubit; A secondary encryption decision unit is used to generate quantum state remodulation trigger coefficients based on the standardized processing results; The instruction generation unit is used to generate a quantum state modulation parameter correction instruction when the quantum state remodulation trigger coefficient exceeds a preset threshold.

8. The data transmission security encryption system of the quantum encryption switch according to claim 7, characterized in that, The secondary encryption decision unit includes: The transmission feature extraction subunit is used to calculate the quantum key verification failure rate and data packet retransmission rate; The decision model processing subunit is used to process the quantum key verification failure rate and data packet retransmission rate through the principal component discrimination model. The threshold comparison subunit is used to compare the output of the principal component discrimination model with a preset security threshold to generate quantum state remodulation trigger coefficients.

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