A method for strengthening password security based on confidential communication

Abstract

The invention discloses a cryptographic security enhancement method based on confidential communication, which specifically relates to the technical field of cryptographic security. The method realizes the transmission of quantum states and information negotiation by constructing quantum communication channels and classical communication channels. After photon encoding and transmission, the photon time delay is analyzed. If the delay is abnormal, a pulsed light source is used to simulate a photon signal, the detector trigger probability is recorded, and the time window deviation is judged. The delay data and the trigger probability deviation are comprehensively evaluated, the security vulnerability risk caused by the non-ideality of the photon detector is quantified, and the risk is divided into high, medium and low levels. Corresponding management is implemented. For the medium risk level, the compression ratio of privacy amplification is dynamically adjusted by using fuzzy logic in combination with the preliminary key bit error rate and the detector risk value, and the anti-eavesdropping capability of the key is enhanced. Through real-time monitoring and dynamic adjustment, the security of the quantum key distribution system is improved, the time offset attack is defended, and the long-term security of encrypted communication is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of password security, and in particular to a password security strengthening method based on confidential communication. Background Art

[0002] Cryptographic security enhancement based on confidential communication refers to preventing data from being stolen or tampered with during transmission by establishing secure communication channels and enhancing the security of cryptographic algorithms, thereby improving the overall security of information systems. Its core idea is to combine encryption technology with secure communication protocols to ensure the confidentiality and integrity of key distribution and data transmission.

[0003] Specifically, on the one hand, this technology protects the communication channel from man-in-the-middle attacks or eavesdropping through encryption protocols (such as TLS / SSL) or quantum key distribution, ensuring the secure transmission of keys and sensitive data; on the other hand, it enhances the anti-attack capability of cryptographic algorithms, such as increasing key length, optimizing random number generators, or combining dynamic encryption mechanisms, fundamentally reducing the success rate of side channel attacks. The goal of this approach is to ensure that data remains secure and reliable in a complex threat environment through double protection.

[0004] The prior art has the following deficiencies:

[0005] Quantum key distribution relies on strict time control of quantum states, but attackers can introduce microsecond time offsets and use the time windows of non-ideal photon detectors to hijack and analyze photon transmissions, thereby stealing keys without triggering eavesdropping detection mechanisms. For example, by adjusting the arrival time of photons, attackers can cause legitimate devices to misjudge whether the photon state is being eavesdropped. Because these vulnerabilities stem from the characteristics of physical devices and are difficult to fix through software or protocols, attackers can steal all keys without the communication parties noticing, which in turn leads to the exposure of all subsequent encrypted data. At the same time, attackers can steal all keys during the key generation phase and completely destroy the confidentiality of the keys without the communication parties knowing, making subsequent encrypted communications meaningless. Once the key is leaked, the attacker can decrypt in real time or store and delay the decryption of the transmitted information, bringing a long-term and irreversible security crisis. Summary of the invention

[0006] The purpose of the present invention is to provide a cryptographic security enhancement method based on confidential communication to address the deficiencies in the background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solution: a method for strengthening password security based on confidential communication, comprising the following steps:

[0008] S1: Constructing a quantum communication channel and a classical communication channel, wherein the quantum communication channel is used to transmit the quantum state of a single photon; and the classical communication channel is used to negotiate and verify information;

[0009] S2: Alice generates a series of quantum states, encodes each photon according to the predetermined quantum key distribution protocol, transmits the encoded photons to Bob through the quantum communication channel, and analyzes the time delay between the photon emission from Alice to the detector at Bob.

[0010] S3: If the delay is high, a pulsed light source is used to simulate a photon signal, which is input into the detector at different time intervals. The triggering probability of the detector for the photon signal is recorded and analyzed to determine the degree of deviation of the triggering probability of the detector in different time windows.

[0011] S4: Comprehensively analyze the time delay between the photon emission from Alice to the detector at Bob and the trigger probability deviation of the detector in different time windows to evaluate the risk of security vulnerabilities caused by the non-ideality of the photon detector in the quantum key distribution system;

[0012] S5: Based on the evaluation results, the risk of security vulnerabilities caused by the non-ideality of the photon detector in the key distribution system is divided into different levels, namely, high risk level, medium risk level and low risk level, and corresponding management is performed;

[0013] S6: For the medium risk level, the bit error rate is calculated after the initial key generation. Based on the calculated bit error rate and the risk of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system, the compression ratio of privacy amplification is dynamically adjusted using fuzzy logic to enhance the key's anti-eavesdropping capability.

[0014] Preferably, in S2, the time delay between the photon emission from Alice to the detector at Bob is analyzed to generate a photon delay anomaly index, and the photon delay anomaly index is obtained by:

[0015] The delay time from the photon emitted by Alice to the photon received by Bob is recorded as a time series ,in represents the transmission delay of the t-th photon; the ARIMA model is defined by three parameters (p, d, q): p: the order of the autoregressive term, d: the difference order, used to make the series stable; q: the order of the sliding average term; the expression of the ARIMA model is: ;in: is the delay value at the current moment, c is a constant term, is the autoregression coefficient, is the sliding average coefficient, is the error term; use the training data to fit the ARIMA model and determine the parameters , and the optimal values ​​of c; use the ARIMA model to predict future photon delay values: ;in, is the predicted photon delay value, and the residual represents the deviation between the actual value and the predicted value, expressed as: ; Standardize the residuals: ; is the mean of the residual sequence, is the standard deviation of the residual sequence, is the normalized residual value, and the absolute value of the residual is used as the photon delay anomaly index.

[0016] Preferably, in S3, after analyzing the peak deviation of the trigger probability distribution curve, a trigger probability peak deviation index is generated, and the method for obtaining the trigger probability peak deviation index is:

[0017] Collected in different time windows The probability of triggering , forming a set of trigger probability distribution data points: ; Use Gaussian function to fit the trigger probability distribution. The fitting function form is: ; Where: A is the maximum trigger probability of the fitting curve, μ is the peak position of the fitting, and σ is the width of the fitting curve;

[0018] Fitting a Gaussian function using nonlinear least squares: Input data , output fitting parameters (A, μ, σ); calculate the fitting peak position μ and the theoretical expected position The absolute deviation is: ; Use the fitting width σ to normalize the deviation, and use the normalized deviation value as the trigger probability peak deviation index, expressed as: ; Where GK is the trigger probability peak deviation index.

[0019] Preferably, in S4, the time delay between the emission of photons from Alice to the detector at Bob and the degree of deviation of the triggering probability of the detector in different time windows are comprehensively analyzed to evaluate the risk of security vulnerabilities caused by the non-ideality of the photon detector in the quantum key distribution system, specifically:

[0020] The photon delay anomaly index and the trigger probability peak deviation index are converted into comprehensive feature vectors, and the comprehensive feature vectors are used as the input of the machine learning model. The machine learning model predicts the risk value label of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system with each group of comprehensive feature vectors as the prediction target, and minimizes the sum of the prediction errors of the risk value labels of the security vulnerability caused by the non-ideality of the photon detector in all quantum key distribution systems as the training target. The machine learning model is trained until the sum of the prediction errors converges and the model training is stopped. The risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0021] Preferably, in S5, according to the evaluation result, the risk of security vulnerabilities caused by the non-ideality of the photon detector in the key distribution system is divided into different levels, namely, high risk level, medium risk level and low risk level, specifically:

[0022] The obtained risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is compared with the gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is compared with the first standard threshold and the second standard threshold respectively;

[0023] If the risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is greater than the second standard threshold, it means that the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is high, and a high risk signal is generated at this time, and the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is classified as a high risk level;

[0024] If the risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, it means that the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is average, and a medium risk signal is generated at this time, and the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is classified as a medium risk level;

[0025] If the risk value of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is less than the first standard threshold, it means that the risk of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is low. At this time, a low-risk signal is generated, and the risk of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is classified as a low risk level.

[0026] Preferably, in S6, for the medium risk level, the bit error rate is calculated after the preliminary key generation, and based on the calculated bit error rate and the risk of security vulnerabilities caused by the non-ideality of the photon detector in the quantum key distribution system, the compression ratio of the privacy amplification is dynamically adjusted after using fuzzy logic, specifically:

[0027] The bit error rate QBER and the risk value LR of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system are used as input items of fuzzy logic, and the privacy amplification compression ratio PR is used as the output item of fuzzy logic;

[0028] The input items and output items are fuzzified, and a fuzzy rule base is constructed according to the combination relationship of QBER and LR. The membership degree of each fuzzy rule is calculated according to the actual values ​​of input QBER and LR.

[0029] Combine the activation memberships of all rules to generate the fuzzy output membership of PR;

[0030] Defuzzification using weighted average method: ;in: is the quantized value of the output language variable, is the corresponding membership degree.

[0031] Preferably, according to the defuzzified PR value, the level at which the privacy amplification compression ratio needs to be set is determined to enhance security, specifically:

[0032] Will The value range of is divided into different privacy amplification compression ratio levels, each level corresponds to the strength of privacy amplification: Low compression ratio: ; Medium compression ratio: ; High compression ratio: ;

[0033] according to In the range where the privacy amplification is located, a specific privacy amplification compression ratio parameter f is selected for privacy amplification calculation. The privacy amplification compression ratio formula is: ;in: The final key length after privacy amplification, is the initial key length, is the amount of information obtained by the eavesdropper, f is the compression rate of privacy amplification, and correspond.

[0034] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0035] 1. The present invention constructs quantum communication channels and classical communication channels, combines time delay analysis and trigger probability assessment, and conducts comprehensive risk assessment and dynamic management of security vulnerabilities caused by the non-ideality of photon detectors in the process of quantum key distribution. The photon delay anomaly index is generated by the ARIMA model, and the trigger probability peak deviation index is generated by Gaussian fitting. The two are input into the polynomial regression model as comprehensive feature vectors to predict and grade the risk of security vulnerabilities of photon detectors. For medium risk levels, based on the bit error rate and the detector risk value, fuzzy logic is used to dynamically adjust the compression ratio of privacy amplification to ensure the anti-eavesdropping capability of the key and the security of encrypted communications.

[0036] 2. The present invention can effectively detect and resist microsecond-level time shift attacks, significantly reduce the risk of key leakage caused by detector non-ideality, and achieve a balance between security and key distribution efficiency by dynamically adjusting the privacy amplification intensity. Compared with traditional methods, the present invention not only improves the security performance of the quantum key distribution system, but also enhances its ability to adapt to complex threat environments, providing an efficient and reliable technical solution for the field of quantum communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0038] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] For examples, see Figure 1 As shown, the password security enhancement method based on confidential communication described in this embodiment includes the following steps:

[0041] S1: Constructing a quantum communication channel and a classical communication channel, wherein the quantum communication channel is used to transmit the quantum state of a single photon; and the classical communication channel is used to negotiate and verify information;

[0042] S2: Alice generates a series of quantum states, encodes each photon according to the predetermined quantum key distribution protocol, transmits the encoded photons to Bob through the quantum communication channel, and analyzes the time delay between the photon emission from Alice to the detector at Bob.

[0043] S3: If the delay is high, a pulsed light source is used to simulate a photon signal, which is input into the detector at different time intervals. The triggering probability of the detector for the photon signal is recorded and analyzed to determine the degree of deviation of the triggering probability of the detector in different time windows.

[0044] S4: Comprehensively analyze the time delay between the photon emission from Alice to the detector at Bob and the trigger probability deviation of the detector in different time windows to evaluate the risk of security vulnerabilities caused by the non-ideality of the photon detector in the quantum key distribution system;

[0045] S5: Based on the evaluation results, the risk of security vulnerabilities caused by the non-ideality of the photon detector in the key distribution system is divided into different levels, namely, high risk level, medium risk level and low risk level, and corresponding management is performed;

[0046] S6: For the medium risk level, the bit error rate is calculated after the initial key generation. Based on the calculated bit error rate and the risk of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system, the compression ratio of privacy amplification is dynamically adjusted using fuzzy logic to enhance the key's anti-eavesdropping capability.

[0047] In S1, a quantum communication channel and a classical communication channel are constructed. The quantum communication channel is used to transmit the quantum state of a single photon; the classical communication channel is used to negotiate and verify information, specifically:

[0048] Quantum communication channels are used to transmit quantum states (for example, polarization or phase information of single photons). Their design needs to meet the basic principles of quantum mechanics to ensure that eavesdropping can be detected. Channel media include: Fiber channel: Using optical fiber as a medium for quantum state transmission, it has low loss and high transmission efficiency, and is suitable for medium and long-distance quantum communication. Free space channel: Transmitting quantum signals through the atmosphere, suitable for short-distance or inter-satellite communication, but susceptible to atmospheric disturbances and optical losses. The selection of quantum states includes: Polarization state encoding: Using horizontal, vertical, or diagonal polarization of photons to represent quantum bits (such as the BB84 protocol). Phase encoding: Controlling the phase of photons through an interferometer to encode key information. Random basis state selection: The sender (Alice) randomly selects the basis state (such as horizontal / vertical or diagonal basis) to avoid being predicted by attackers.

[0049] Quantum signals are susceptible to ambient light, scattering, or line loss. Optical filtering and signal amplification are required to reduce noise interference. After a certain distance (usually tens to hundreds of kilometers), the intensity of photon signals drops significantly, which can be expanded through relay nodes or quantum entanglement distribution. According to the principle of quantum non-cloning, any eavesdropping behavior will change the quantum state and introduce bit error rate, and abnormalities will be detected through bit error detection. Typical methods include checking whether the bit error rate caused by eavesdropping exceeds the safety threshold.

[0050] The classical communication channel is an auxiliary channel of the quantum key distribution system, which is used for the exchange and confirmation of information between the two parties. It does not need to have quantum characteristics, but it needs to ensure the integrity and authenticity of the communication. Traditional communication network: a classical data transmission network based on optical fiber, wireless or Ethernet. Secure transmission protocol: a secure and authenticated communication protocol (such as TLS) is used to protect data transmission and prevent tampering or man-in-the-middle attacks.

[0051] Alice and Bob exchange ground state selection information through the classical channel, eliminating qubits with different measured ground states. Both parties disclose some preliminary key bits to calculate the bit error rate and evaluate whether the channel is secure. Both parties negotiate privacy amplification and information correction algorithms through the classical channel to weaken the information that eavesdroppers may obtain. Both parties exchange data verification information in the classical channel to ensure that the final key is completely consistent. The authenticity of the communicating parties is ensured through digital signatures or other authentication technologies to prevent middleman impersonation attacks. In the classical channel, information can be encrypted and transmitted using the initially generated key to further improve security.

[0052] The cooperation between quantum communication channel and classical communication channel is the key to the successful operation of QKD. Their division of labor and cooperation are as follows:

[0053] Quantum communication channel: responsible for the transmission of core quantum states and is the physical basis for key generation.

[0054] Classic communication channel: responsible for key negotiation and confirmation, and is a logical supplement to ensure security and consistency.

[0055] In this application, the quantum state of a single photon is transmitted through a quantum channel, and key negotiation, error detection, and privacy amplification are completed in combination with a classical channel, so that both parties can finally share a consistent key securely. The reliability of the classical channel is the guarantee of the entire QKD process, and the un-eavesdropping nature of the quantum channel is the core of the system security.

[0056] S2: Alice generates a series of quantum states, encodes each photon according to the predetermined quantum key distribution protocol, transmits the encoded photons to Bob through the quantum communication channel, and analyzes the time delay between the photon emission from Alice to the detector at Bob.

[0057] According to a predetermined quantum key distribution protocol (such as the BB84 protocol), Alice selects the type of quantum state for encoding. Polarization state encoding: Photons use four polarization states (such as horizontal, vertical, +45°, and -45°) to represent quantum bits. Phase encoding: The phase of photons is controlled by an interferometer to form different quantum states. Alice randomly selects a basis state (such as a straight basis state and a diagonal basis state) to encode each photon, ensuring that the measurement results are difficult to predict. Alice uses a single photon source (or a weak coherent light source close to a single photon) to generate photons. Each photon is encoded by a polarization modulator or a phase modulator to carry the target quantum information.

[0058] Alice generates and transmits coded photons one by one according to the protocol. During the transmission process, the precise time of photon emission (reference clock) is recorded to provide a benchmark for subsequent time delay analysis. Photons are transmitted to Bob through a quantum communication channel (such as optical fiber or free space). Since photon transmission may be affected by channel noise, scattering or loss, Alice and Bob need to use a classical communication channel to negotiate information and compensate for random interference in the channel.

[0059] Alice and Bob need to perform high-precision time synchronization and maintain a consistent time base through a reference clock. Time synchronization is crucial for subsequent time delay analysis, and any time deviation will affect the validity of the measurement results. Alice records the timestamp of the photon emission, and Bob records the timestamp of the photon arriving at the detector. Through the classical communication channel, Alice and Bob exchange recorded data.

[0060] The photon delay anomaly index is generated by analyzing the time delay between the photon emitted from Alice to the detector at Bob. The photon delay anomaly index is obtained as follows:

[0061] The delay time from the photon emitted by Alice to the photon received by Bob is recorded as a time series ,in Represents the transmission delay of the tth photon. Ensure that the data has a time sequence and the sampling intervals are equal (such as recording the average delay once per second); detect whether the time series is stationary (the mean and variance remain unchanged over time), and use the ADF test (Augmented Dickey-Fuller Test) to judge. If the series is non-stationary, the data is differenced to make it stationary. The ARIMA model is defined by three parameters (p, d, q): p: the order of the autoregressive (AR) term. d: the difference order, used to make the series stationary. q: the order of the moving average (MA) term. Choose d: Make the series stationary by difference, usually d=1 or d=2. Choose p and q: Determine the appropriate order by analyzing the autocorrelation function (ACF) and partial autocorrelation function (PACF) graphs of the series: ACF is used to estimate q, and PACF is used to estimate p. The expression of the ARIMA model is: ;in: is the delay value at the current moment, c is a constant term, is the autoregression coefficient (AR part), is the sliding average coefficient (MA part), is the error term (white noise).

[0062] Fit the ARIMA model using the training data (historical photon delay time series) and determine the parameters , and the optimal values ​​of c; use the ARIMA model to predict future photon delay values: ;in, is the predicted photon delay value. The residual represents the deviation between the actual value and the predicted value, and the expression is: ; Standardize the residuals: ; is the mean of the residual sequence, is the standard deviation of the residual sequence, is the normalized residual value, and the absolute value of the residual is used as the photon delay anomaly index.

[0063] The larger the photon delay anomaly index is, the more the time delay between the photon emitted from Alice and the detector at Bob deviates from the normal range, indicating that the current photon transmission is abnormal. This may be caused by channel interference, equipment failure, or potential attacks (such as time offset attacks). A larger anomaly index usually indicates that the delay time deviates significantly from the predicted value. For example, a long delay may indicate channel congestion or an attacker trying to manipulate the photon transmission process, while a short delay may be related to abnormal behavior within the system (such as a false triggering of the detector).

[0064] The smaller the photon delay anomaly index is, the closer the time delay between the photon emission from Alice to the detector at Bob is to the normal range, and the system is running stably without obvious anomalies. At this time, the photon delay value is in line with the expected range of historical data and prediction models, indicating that the communication channel has less interference, the equipment is running well, and the quantum key distribution process is safe and reliable. A smaller anomaly index is a sign of ideal system security and performance, and both parties can rest assured to conduct key negotiation and subsequent encrypted communications.

[0065] S3: If the delay is high, a pulsed light source is used to simulate a photon signal, which is input into the detector at different time intervals. The triggering probability of the detector for the photon signal is recorded and analyzed to determine the degree of deviation of the triggering probability of the detector in different time windows.

[0066] If the time delay between the photon emission from Alice to the detector at Bob deviates from the normal range, use a pulsed light source to simulate the photon signal, use a controllable pulsed light source instead of the actual photon, and accurately adjust the time when the photon arrives at the detector to observe the triggering performance of the detector. Set the time reference of the pulsed light source to synchronize it with the time reference of the detector. Simulate different delays of the photon signal and set a series of time intervals (for example, from 0 to the maximum delay range, increasing by a fixed step size). Transmit the simulated photon signal to the detector at a fixed intensity.

[0067] The ratio of the number of times the detector responds to the photon signal to the total number of inputs indicates the detector's ability to respond to the photon signal. At each set time interval, send multiple simulated photon signals (such as 100 times) and record the number of times the detector is triggered. Calculate the trigger probability corresponding to each time interval: ; Match the trigger probability with the time interval to form a set of data points, and plot the trigger probability corresponding to different time intervals into a curve. Observe whether the peak, width and shape of the curve are symmetrical. If the peak of the trigger probability distribution curve is not in the expected time window (such as the center of the delay), it means that the detector's response to the photon signal has a time drift.

[0068] After analyzing the peak deviation of the trigger probability distribution curve, a trigger probability peak deviation index is generated. The method for obtaining the trigger probability peak deviation index is as follows:

[0069] Collected in different time windows The probability of triggering , forming a set of trigger probability distribution data points: ; Use Gaussian function to fit the trigger probability distribution. The fitting function form is: ; Where: A is the maximum trigger probability (amplitude) of the fitting curve, μ is the peak position of the fitting (center of the time window), and σ is the width (standard deviation) of the fitting curve, reflecting the degree of diffusion of the distribution.

[0070] Fit a Gaussian function using nonlinear least squares or other optimization methods such as the Levenberg-Marquardt algorithm: Input data , output fitting parameters (A, μ, σ). Calculate the fitting peak position μ and the theoretical expected position The absolute deviation is: ; In order to make the deviation amount have uniform comparability, the deviation is normalized using the fitting width σ, and the normalized deviation value is used as the trigger probability peak deviation index, which is expressed as: ; Where GK is the trigger probability peak deviation index.

[0071] The larger the trigger probability peak deviation index is, the more serious the deviation of the detector's trigger probability is in different time windows. This indicates that the peak position of the trigger probability distribution deviates significantly from theoretical expectations, which may cause the detector to respond to photon signals unstably or inaccurately. A large trigger probability peak deviation index may be caused by system hardware failure, external interference (such as noise or temperature changes), or unreasonable time window settings, which may further lead to an increase in the bit error rate in quantum key distribution, affecting the security and reliability of key generation.

[0072] The smaller the trigger probability peak deviation index, the smaller the trigger probability deviation of the detector in different time windows, indicating that the detector's response to the photon signal is more concentrated and accurate. A smaller trigger probability peak deviation index indicates that the peak position of the trigger probability distribution is close to the theoretical expectation, the detector has good sensitivity within the optimal time window, and the system operation state is stable. In this case, the efficiency and security of quantum key distribution can be effectively guaranteed, indicating that the detector performance is superior and the channel environment interference is small.

[0073] S4: Comprehensively analyze the time delay between the photon emission from Alice to the detector at Bob’s end and the degree of trigger probability deviation of the detector in different time windows to evaluate the risk of security vulnerabilities caused by the non-ideality of the photon detector in the quantum key distribution system.

[0074] The photon delay anomaly index and the trigger probability peak deviation index are converted into comprehensive feature vectors, and the comprehensive feature vectors are used as the input of the machine learning model. The machine learning model predicts the risk value label of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system with each group of comprehensive feature vectors as the prediction target, and minimizes the sum of the prediction errors of the risk value labels of the security vulnerability caused by the non-ideality of the photon detector in all quantum key distribution systems as the training target. The machine learning model is trained until the sum of the prediction errors converges and the model training is stopped. The risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0075] The method for obtaining the risk value of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is to obtain the corresponding function expression from the comprehensive feature vector training data of the trained machine learning model: ; In the formula, F is the output function of the model, HG is the photon delay anomaly index, GK is the trigger probability peak deviation index, and LR is the risk value of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system.

[0076] S5: Based on the evaluation results, the risk of security vulnerabilities caused by the non-ideality of photon detectors in the key distribution system is divided into different levels, namely high risk level, medium risk level and low risk level, and managed accordingly.

[0077] The obtained risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is compared with the gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is compared with the first standard threshold and the second standard threshold respectively;

[0078] If the risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is greater than the second standard threshold, it means that the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is high, and a high risk signal is generated at this time, and the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is classified as a high risk level;

[0079] If the risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, it means that the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is average, and a medium risk signal is generated at this time, and the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is classified as a medium risk level;

[0080] If the risk value of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is less than the first standard threshold, it means that the risk of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is low. At this time, a low-risk signal is generated, and the risk of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is classified as a low risk level.

[0081] High-risk level management: The risk value is greater than the second standard threshold, indicating that the detector non-ideality may seriously affect the security of key distribution, and there are significant vulnerabilities or attack threats. Management measures include: Immediately stop key distribution: suspend current quantum communication to prevent the continued generation of unsafe keys. Generate a high-risk signal to notify the system administrator for emergency processing. Conduct an in-depth analysis of the detector hardware performance (such as response time, sensitivity) and channel environment (such as noise interference). If the problem is caused by the non-ideality of the detector hardware, replace the device immediately. Generate a detailed high-risk assessment report, archive it and use it to optimize the system.

[0082] Medium risk level management: The risk value is between the first standard threshold and the second standard threshold. The non-ideal performance of the detector may cause potential safety hazards, but it has not yet reached a critical level. Management measures include: Strengthen monitoring: Turn on the real-time monitoring mode to record the performance parameters of the detector and the trend of the risk value. According to the real-time data, adjust the key distribution parameters (such as the time window range and the privacy amplification strength) to reduce the risk. Perform performance testing and calibration of the detector during non-working hours to ensure that the error does not expand further. Generate a medium risk signal to prompt the administrator to pay close attention to the system status. Adjust the system parameters according to the diagnosis results to optimize the response performance of the detector.

[0083] Low risk level management: The risk value is less than the first standard threshold, the detector non-idealities have little impact on system safety, and the system is in normal operation. Management measures include: Continue to record the performance parameters of the detector regularly to ensure stable operation of the system. Perform routine maintenance on the detector and system hardware as planned to prevent potential risk accumulation. Use the data analysis results of the low risk stage to further improve the sensitivity and stability of the detector. Generate a low risk operation report and archive it for subsequent evaluation and comparison.

[0084] S6: For the medium risk level, the bit error rate is calculated after the initial key generation. Based on the calculated bit error rate and the risk of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system, the compression ratio of privacy amplification is dynamically adjusted using fuzzy logic to enhance the key's anti-eavesdropping capability.

[0085] Alice and Bob generate preliminary keys through quantum communication channels and classical communication channels respectively. The preliminary key is encoded by Alice and transmitted through the quantum channel, and Bob obtains the original version of the key through measurement. The two parties agree to disclose a certain proportion of the preliminary key bits (for example, 10%-20%) for bit error rate calculation. The public key bits are transmitted through the classical communication channel to ensure that both parties synchronize data. Alice and Bob compare the public preliminary keys bit by bit, record the inconsistent bits (the number of erroneous bits), and count the total number of public bits. The bit error rate QBER calculation formula is: ; Number of error bits: the number of inconsistent bits in Alice and Bob's public keys, total number of public bits: the total number of key bits that Alice and Bob publicly use for comparison.

[0086] The bit error rate QBER and the risk value LR of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system are used as input items of fuzzy logic, and the privacy amplification compression ratio PR is used as the output item of fuzzy logic;

[0087] Fuzzify the input items: Define the fuzzy language variables of QBER: Low: QBER is close to 0, and the bit error rate is at a negligible level. Medium: QBER is within the threshold range, and the system risk is medium. High: QBER significantly exceeds the threshold, and the potential for eavesdropping is high.

[0088] System risk is medium. High: QBER significantly exceeds the threshold, and the potential for eavesdropping is high. Set the QBER fuzzy membership function: ; Similarly defined and Define the fuzzy linguistic variables of LR: Low: The detector performance is close to ideal, and the non-ideal risk is small. Medium: The detector performance has some deviation, but it does not reach a significant risk. High: The detector non-ideality is significant and may lead to serious security vulnerabilities. Set the LR fuzzy membership function, which is similar to QBER.

[0089] Fuzzify the output items and define the fuzzy language variables of PR: Low: low security requirements and low compression ratio. Medium: a compression ratio that balances efficiency and security. High: requires high-intensity privacy amplification to minimize the eavesdropper's information.

[0090] PR fuzzy membership function: ; described by designing similar trapezoidal or triangular membership functions.

[0091] According to the combination relationship of QBER and LR, a fuzzy rule base is constructed, as shown below: Rule 1: If QBER is low and LR is low, then PR is low. Rule 2: If QBER is low and LR is medium, then PR is medium. Rule 3: If QBER is high and LR is high, then PR is high. Rule 4: If QBER is medium and LR is high, then PR is high. Rule 5: If QBER is medium and LR is medium, then PR is medium.

[0092] Calculate the activation strength (membership degree) of each fuzzy rule based on the actual values ​​of input QBER and LR. Example: QBER = 4%, LR = 70. ;

[0093] Perform fuzzy logic operations (such as minimum value method) on the membership of each rule: For rule 3 (if QBER is high and LR is high, then PR is high): .

[0094] The activation memberships of all rules are combined to generate the fuzzy output membership of PR.

[0095] Defuzzification using weighted average method: ;in: is the quantitative value of the output language variable (such as low = 0.2, medium = 0.5, high = 0.8), is the corresponding membership degree.

[0096] According to the defuzzified PR value, the level of privacy amplification compression ratio that needs to be set is determined to enhance security, specifically:

[0097] Will The value range of is divided into different privacy amplification compression ratio levels, each level corresponds to the strength of privacy amplification:

[0098] Low compression ratio: ; The system is in a low risk state, the compression ratio is low, and the key generation efficiency is prioritized. Medium compression ratio: ; The system has certain risks, balancing security and key generation efficiency. High compression ratio: ; The system is in a high-risk state, the compression ratio is set to high intensity, and safety is prioritized.

[0099] according to In the range, select a specific privacy amplification compression ratio parameter f (specific value of the compression ratio) for privacy amplification calculation: Privacy amplification compression ratio formula: ;in: The final key length after privacy amplification, is the initial key length, is the amount of information that an eavesdropper may obtain, f is the compression rate of privacy amplification, and Corresponding. Privacy amplification compression ratio examples: Low compression ratio: f=1.1. Medium compression ratio: f=1.3. High compression ratio: f=1.5.

[0100] According to the defuzzified ,By mapping the compression ratio level of privacy amplification, the parameter f is dynamically adjusted to achieve a balance between efficiency and security. In high-risk situations, a high compression ratio is used to weaken the amount of information of the eavesdropper; in low-risk situations, the compression ratio is reduced to improve the efficiency of key generation.

[0101] In this embodiment, in the quantum key distribution system, by constructing a quantum communication channel and a classical communication channel, the transmission of single-photon quantum states and information negotiation verification are realized. Alice generates a series of quantum states, encodes photons according to the protocol and transmits them to Bob, and analyzes the time delay between the photons emitted from Alice to the detector at Bob. If the delay is high, a pulsed light source is used to simulate the photon signal, input the detector at different time intervals, record and analyze the trigger probability, and judge the degree of deviation of the trigger probability of the detector in different time windows. By comprehensively analyzing the time delay and the trigger probability deviation, the risk of security vulnerabilities caused by the non-ideality of the photon detector is evaluated. According to the evaluation results, the risk is divided into three levels: high, medium and low, and hierarchical management is performed. For the medium risk level, the bit error rate of the preliminary key is calculated, and based on the bit error rate and the risk value of the detector non-ideality, the compression ratio of the privacy amplification is dynamically adjusted through fuzzy logic to enhance the anti-eavesdropping ability of the key.

[0102] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0103] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0104] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the objects associated with each other are in an "or" relationship, but it may also indicate an "and / or" relationship, which can be understood by referring to the context. A person of ordinary skill in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this article can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0105] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for strengthening password security based on confidential communication, characterized in that: The steps include: S1: Constructing a quantum communication channel and a classical communication channel, wherein the quantum communication channel is used to transmit the quantum state of a single photon; and the classical communication channel is used to negotiate and verify information; S2: Alice generates a series of quantum states, encodes each photon according to a predetermined quantum key distribution protocol, transmits the encoded photons to Bob through a quantum communication channel, and analyzes the time delay between the photon emission from Alice to the detector at Bob. S3: If the delay is high, a pulsed light source is used to simulate a photon signal, which is input into the detector at different time intervals. The triggering probability of the detector for the photon signal is recorded and analyzed to determine the degree of deviation of the triggering probability of the detector in different time windows. S4: Comprehensively analyze the time delay between the photon emission from Alice to the detector at Bob and the trigger probability deviation of the detector in different time windows to evaluate the risk of security vulnerabilities caused by the non-ideality of the photon detector in the quantum key distribution system; S5: Based on the evaluation results, the risk of security vulnerabilities caused by the non-ideality of the photon detector in the key distribution system is divided into different levels, namely, high risk level, medium risk level and low risk level, and corresponding management is performed; S6: For the medium risk level, the bit error rate is calculated after the initial key generation. Based on the calculated bit error rate and the risk of security vulnerabilities caused by the non-ideality of the photon detector in the quantum key distribution system, the compression ratio of the privacy amplification is dynamically adjusted after using fuzzy logic to enhance the key's anti-eavesdropping capability. The step S6 specifically includes: taking the bit error rate QBER and the risk value LR of security vulnerabilities caused by the non-ideality of the photon detector in the quantum key distribution system as input items of the fuzzy logic, and taking the privacy amplification compression ratio PR as the output item of the fuzzy logic; The input items and output items are fuzzified, and a fuzzy rule base is constructed according to the combination relationship of QBER and LR. The membership degree of each fuzzy rule is calculated according to the actual values ​​of input QBER and LR. Combine the activation memberships of all rules to generate the fuzzy output membership of PR; Defuzzification using weighted average method: ;in: is the quantized value of the output language variable, is the corresponding membership degree; According to the defuzzified PR value, the level of privacy amplification compression ratio that needs to be set is determined to enhance security, specifically: Will The value range of is divided into different privacy amplification compression ratio levels, each level corresponds to the strength of privacy amplification: Low compression ratio: ; Medium compression ratio: ; High compression ratio: ; according to In the range where the privacy amplification is located, a specific privacy amplification compression ratio parameter f is selected for privacy amplification calculation. The privacy amplification compression ratio formula is: ;in: The final key length after privacy amplification, is the initial key length, is the amount of information obtained by the eavesdropper, f is the compression rate of privacy amplification, and correspond.

2. According to claim 1, a method for strengthening password security based on confidential communication is characterized in that: In S2, the time delay between the photon emission from Alice to the detector at Bob is analyzed to generate a photon delay anomaly index. The photon delay anomaly index is obtained as follows: The delay time from the photon emitted by Alice to the photon received by Bob is recorded as a time series ,in represents the transmission delay of the t-th photon; the ARIMA model is defined by three parameters (p, d, q): p: the order of the autoregressive term, d: the difference order, used to make the series stable; q: the order of the moving average term; the expression of the ARIMA model is: ;in: is the delay value at the current moment, c is a constant term, is the autoregression coefficient, is the sliding average coefficient, is the error term; use the training data to fit the ARIMA model and determine the parameters and the optimal values ​​of c; use the ARIMA model to predict future photon delay values: ;in, is the predicted photon delay value, and the residual represents the deviation between the actual value and the predicted value, expressed as: ; Standardize the residuals: ; is the mean of the residual sequence, is the standard deviation of the residual sequence, is the normalized residual value, and the absolute value of the residual is used as the photon delay anomaly index.

3. A method for strengthening password security based on confidential communication according to claim 2, characterized in that: In S3, the peak deviation of the trigger probability distribution curve is analyzed to generate a trigger probability peak deviation index. The method for obtaining the trigger probability peak deviation index is: Collected in different time windows The probability of triggering , forming a set of trigger probability distribution data points: ; Use Gaussian function to fit the trigger probability distribution. The fitting function form is: ; Where: A is the maximum trigger probability of the fitting curve, μ is the peak position of the fitting, and σ is the width of the fitting curve; Fitting a Gaussian function using nonlinear least squares: Input data , output fitting parameters (A, μ, σ); calculate the fitting peak position μ and the theoretical expected position The absolute deviation is: ; Use the fitting width σ to normalize the deviation, and use the normalized deviation value as the trigger probability peak deviation index, expressed as: ; Where GK is the trigger probability peak deviation index.

4. A method for strengthening password security based on confidential communication according to claim 3, characterized in that: In S4, the time delay between the photon emission from Alice to the detector at Bob and the trigger probability deviation of the detector in different time windows are comprehensively analyzed to evaluate the risk of security vulnerabilities caused by the non-ideality of the photon detector in the quantum key distribution system, specifically: The photon delay anomaly index and the trigger probability peak deviation index are converted into comprehensive feature vectors, and the comprehensive feature vectors are used as the input of the machine learning model. The machine learning model predicts the risk value label of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system with each group of comprehensive feature vectors as the prediction target, and minimizes the sum of the prediction errors of the risk value labels of the security vulnerability caused by the non-ideality of the photon detector in all quantum key distribution systems as the training target. The machine learning model is trained until the sum of the prediction errors converges and the model training is stopped. The risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

5. A method for strengthening password security based on confidential communication according to claim 4, characterized in that: In S5, according to the evaluation results, the risk of security vulnerabilities caused by the non-ideality of the photon detector in the key distribution system is divided into different levels, namely high risk level, medium risk level and low risk level, specifically: The obtained risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is compared with the gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is compared with the first standard threshold and the second standard threshold respectively; If the risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is greater than the second standard threshold, it means that the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is high, and a high risk signal is generated at this time, and the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is classified as a high risk level; If the risk value of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, it means that the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is average, and a medium risk signal is generated at this time, and the risk of the security vulnerability caused by the non-ideality of the photon detector in the quantum key distribution system is classified as a medium risk level; If the risk value of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is less than the first standard threshold, it means that the risk of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is low. At this time, a low-risk signal is generated, and the risk of security vulnerabilities caused by the non-ideality of photon detectors in the quantum key distribution system is classified as a low risk level.

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