A method and system for secure storage of electronic information

Abstract

The present invention discloses a method and system for secure storage of electronic information, which specifically relates to the technical field of information storage security, and is used to solve the existing problem of poor stability and consistency of encryption keys generated by PUF under complex and changing environmental conditions; a PUF response is generated by a hardware device under a controlled environment, thereby obtaining an initial encryption key; a quantum decoherence analysis technology based on quantum behavior simulation is used to continuously monitor the stability of the PUF response in the current environment; environmental data around the hardware device is collected in real time, and compared with a preset environmental threshold to evaluate whether the environment is suitable; a self-similarity model is constructed by segmented sampling and Hurst index analysis of the PUF response signal, and the stability and consistency of the PUF response signal are further evaluated; and finally, a comprehensive analysis is performed to determine whether an encryption key is generated, thereby significantly improving the security of key generation and management.

Description

Technical Field

[0001] The present invention relates to the field of information storage security technology, and more specifically, to a method and system for electronic information security storage. Background Art

[0002] PUF (Physical Unclonable Function) is a security technology that uses the inherent physical irregularities of hardware devices to generate unique responses. The core idea of ​​PUF is to use physical randomness at the microscopic level, such as the inevitable small differences in the semiconductor manufacturing process, to create unique features or "fingerprints" for each chip or device. PUF is able to generate unique responses based on its inherent physical properties, which can be used directly as keys or for generating keys. Since these keys are derived directly from the physical characteristics of the hardware, they do not need to be pre-stored in the device, reducing the risk of key theft or leakage. In the secure storage of electronic information, keys generated using PUF can be used to encrypt data to ensure the confidentiality and integrity of the data.

[0003] In traditional electronic information security storage methods, key generation and management usually rely on software algorithms or pre-stored keys, which makes the system vulnerable to software attacks and physical attacks. If the stability and consistency of encryption keys generated using PUF are poor under complex and changing environmental conditions, it will lead to reduced key reliability, increased data security risks, and decreased system trust, affecting the security of electronic information storage.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a method and system for secure storage of electronic information to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for securely storing electronic information comprises the following steps:

[0008] S1: Generate PUF response from hardware device under controlled environmental conditions to obtain initial encryption key;

[0009] S2: Through quantum decoherence analysis based on quantum behavior simulation, continuously determine whether the PUF is stable in the current environment;

[0010] S3: Collect environmental data around the hardware device in real time; determine whether the current environment of the hardware device is within an acceptable and stable range by comparing the environmental data with the preset environmental threshold;

[0011] S4: By performing segmented sampling on the PUF response signal, a self-similarity model is constructed based on the Hurst exponent, and the self-similarity parameter is calculated to evaluate the stability and consistency of the PUF response signal;

[0012] S5: When the PUF is stable in the current environment, the current environment of the hardware device is within an acceptable stability range, and the PUF response signal has good stability and consistency in the current environment, the PUF response is used to generate an encryption key; otherwise, a predetermined error correction algorithm is applied to the PUF response to correct the initial encryption key.

[0013] In a preferred embodiment, S1 specifically includes:

[0014] S101: Start the hardware device in a controlled environment;

[0015] S102: Triggering the PUF module through a control signal to prepare to generate a unique physical response;

[0016] S103: Using an acquisition circuit to read and digitally process the physical response signal output by the PUF module;

[0017] S104: Based on the collected PUF response signal, a unique initial encryption key is generated by a predetermined algorithm.

[0018] In a preferred embodiment, S2 specifically includes:

[0019] S201: Construct a quantum behavior simulation model based on current environmental parameters to simulate the performance of PUF response in the quantum system;

[0020] S202: Calculate the decoherence time of the PUF response by quantum decoherence analysis to quantify the PUF stability;

[0021] S203: Match the decoherence analysis result with the current environment data to evaluate the impact of the environment on the PUF response;

[0022] S204: Based on the decoherence time and the environment matching result, a decoherence stability judgment value is calculated, and the PUF state is continuously monitored.

[0023] In a preferred embodiment, S204 specifically includes: based on the decoherence time Match the results with the environmental parameters and calculate the decoherence stability judgment value , whose expression is: ;in, and Decoherence time and the weight coefficient of the environment matching function; is the environment matching function;

[0024] Setting the stability threshold ;when When , the PUF is determined to be stable in the current environment; when , then it is determined that PUF is unstable in the current environment.

[0025] In a preferred embodiment, S3 is specifically:

[0026] Set a preset environmental threshold and compare the environmental parameters collected in real time with the preset environmental threshold respectively;

[0027] When all environmental parameters simultaneously meet their corresponding threshold conditions, it is determined that the current environment of the hardware device is within the acceptable stable range; otherwise, it is determined that the current environment of the hardware device is not within the acceptable stable range;

[0028] Among them, environmental parameters include temperature, electromagnetic interference intensity and voltage.

[0029] In a preferred embodiment, S4 specifically includes:

[0030] S401: performing denoising and standardization processing on the collected PUF response signal;

[0031] S402: Segmentally sample the PUF response signal at preset time intervals to obtain signal segments at multiple time scales;

[0032] S403: Use the Hurst index to construct a self-similarity analysis model of the signal to quantify the similarity of the signal at different scales: Use the rescaled range analysis to calculate the Hurst index, and the formula is as follows: ;in, It is on the time scale The signal is extremely poor. is the standard deviation of the signal segment, is a proportionality constant, which is related to the amplitude of the specific signal; is the Hurst exponent;

[0033] S404: Based on the self-similarity analysis model, calculate the self-similarity parameter to measure the scale-invariant property of the signal: calculate the self-similarity parameter , the formula is as follows: ;in, is the self-similarity parameter, is the total number of time scales, It is in Time scale The Hurst exponent calculated on is the number of the time scale;

[0034] S405: Evaluate the stability and consistency of the PUF response signal in the current environment by comparing the calculated self-similarity parameters:

[0035] Preset stability threshold of self-similarity parameter ;if ; It is determined that the PUF response signal has good stability and consistency in the current environment;

[0036] if , it is determined that the PUF response signal is not stable and consistent in the current environment.

[0037] In another aspect, the present invention provides an electronic information security storage system, including a key generation module, a stability analysis module, an environment monitoring module, a signal analysis module, and a key decision module;

[0038] Key generation module: Generates PUF response from hardware devices under controlled environmental conditions to obtain initial encryption keys;

[0039] Stability analysis module: Through quantum decoherence analysis based on quantum behavior simulation, it continuously determines whether the PUF is stable in the current environment;

[0040] Environmental monitoring module: collects environmental data around hardware devices in real time; determines whether the current environment of the hardware device is within an acceptable and stable range by comparing the environmental data with the preset environmental threshold;

[0041] Signal analysis module: Through segmented sampling of PUF response signals, a self-similarity model is constructed based on the Hurst exponent, and self-similarity parameters are calculated to evaluate the stability and consistency of PUF response signals;

[0042] Key decision module: When the PUF is stable in the current environment, the current environment of the hardware device is within an acceptable stability range, and the PUF response signal has good stability and consistency in the current environment, the PUF response is used to generate an encryption key; otherwise, a predetermined error correction algorithm is applied to the PUF response to correct the initial encryption key.

[0043] The technical effects and advantages of the electronic information security storage method and system of the present invention are as follows:

[0044] 1. By generating PUF responses in a controlled environment to generate initial encryption keys, combined with quantum decoherence analysis technology, the stability of PUF is continuously evaluated, which ensures the reliability and security of encryption keys. Due to the uniqueness and unclonability of PUF, the key of each device is inherently unique and cannot be copied, which greatly enhances the security level of the key. In addition, even if the device is physically accessed, since the key is generated directly from the physical properties of the hardware and does not need to be stored in any form of digital media, it avoids the security vulnerabilities and attack vectors that traditional key storage may face.

[0045] 2. By monitoring environmental conditions in real time and comparing them with preset thresholds, as well as analyzing the self-similarity of PUF responses, the stability of PUF and the consistency of response in the entire device operating environment are ensured. This method not only improves the system's adaptability to environmental changes, but also further verifies the stability of the signal through self-similarity analysis, providing double protection for the encryption key finally generated. When the PUF response shows instability, a predetermined error correction algorithm is used to correct the key, which increases the robustness of the system and maintains the security and effectiveness of the encryption key even under undesirable environmental conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A schematic diagram of a method for securely storing electronic information according to the present invention;

[0047] Figure 2 The present invention is a schematic diagram of the structure of an electronic information security storage system. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0049] Example 1

[0050] Figure 1 The present invention provides a method for securely storing electronic information, which comprises the following steps:

[0051] S1: Generate a PUF response from a hardware device under controlled environmental conditions to obtain an initial encryption key.

[0052] S2: Through quantum decoherence analysis based on quantum behavior simulation, continuously determine whether the PUF is stable in the current environment.

[0053] S3: Collect environmental data around the hardware device in real time; determine whether the current environment of the hardware device is within an acceptable and stable range by comparing the environmental data with a preset environmental threshold.

[0054] S4: By performing segmented sampling on the PUF response signal, a self-similarity model is constructed based on the Hurst exponent, and the self-similarity parameters are calculated to evaluate the stability and consistency of the PUF response signal.

[0055] S5: When the PUF is stable in the current environment, the current environment of the hardware device is within an acceptable stability range, and the PUF response signal has good stability and consistency in the current environment, the PUF response is used to generate an encryption key; otherwise, a predetermined error correction algorithm is applied to the PUF response to correct the initial encryption key.

[0056] S1 specifically includes:

[0057] S101: Start the hardware device in a controlled environment to ensure that parameters such as temperature and voltage are stable to facilitate the generation of subsequent PUF responses:

[0058] Use a thermostat to set the operating environment temperature of the hardware device to the optimal operating range (e.g. 25°C ± 2°C) to prevent the impact of external temperature changes on the PUF response signal.

[0059] When starting the device, the voltage regulator circuit adjusts and maintains the power supply voltage within a stable value range (such as 3.3V±0.05V) to prevent response deviation caused by voltage fluctuations.

[0060] In order to eliminate electromagnetic interference, the device uses a shielding device or a low-noise power module when working to ensure that the electromagnetic interference around the device is below the preset threshold (such as below -40dB).

[0061] After the device is started, it executes a self-test procedure to ensure that the hardware modules (such as sensors and signal processing modules) are working properly, and generates a self-test report to record the stability of the current environmental parameters.

[0062] S102: Trigger the PUF module through a control signal to prepare to generate a unique physical response:

[0063] A microcontroller or signal processing unit is used to send a predetermined trigger signal to the PUF module. This trigger signal can be a voltage pulse or a current signal of a specific frequency, with a typical value of a single pulse voltage of 3.3V.

[0064] After receiving the trigger signal, the PUF module begins to generate a physical response based on its physical structure (such as tiny differences in silicon crystals). The time for PUF response generation is usually in nanoseconds, and the response process must be strictly controlled to ensure accurate utilization of physical differences.

[0065] S103: Using the acquisition circuit to read and digitize the physical response signal output by the PUF module:

[0066] The analog response signal output by the PUF is sampled by a high-speed analog-to-digital converter (ADC). The resolution of the ADC is generally set to 12 bits or more to ensure high-precision capture of the physical response. The sampling frequency should be set within a range that can capture all key details of the PUF response (such as 1 MHz or higher).

[0067] In order to ensure the readability of the signal, the acquisition circuit usually integrates an amplifier or gain control module to dynamically adjust the amplitude of the acquired signal to ensure that the signal is within an appropriate range for subsequent processing. During the signal acquisition process, in order to further eliminate the residual noise signal, digital filtering technology is used to process the acquired signal. Common methods include Kalman filtering or low-pass filtering to ensure that the extracted response signal has a high signal-to-noise ratio.

[0068] S104: Based on the collected PUF response signal, a unique initial encryption key is generated through a predetermined algorithm:

[0069] The digitized PUF response signal is encoded using a hash function (such as SHA-256) or a linear feedback shift register (LFSR) to reduce the impact of noise in the physical response and ensure the uniqueness of the output key. This process can be implemented in hardware or software.

[0070] The key length is set according to security requirements, usually 128 bits or 256 bits. The generated key meets the predetermined length requirement by intercepting or extending the PUF response.

[0071] To ensure the uniqueness of the key generated by each hardware device, a collision detection mechanism is used to prevent multiple devices from generating the same key. By comparing the historical key database, the uniqueness of the currently generated key is verified.

[0072] The generated initial encryption key is securely stored via a hardware security module (such as a TPM) or encrypted storage to prevent unauthorized access and modification.

[0073] S2 specifically includes:

[0074] S201: Construct a quantum behavior simulation model based on current environmental parameters to simulate the performance of PUF response in the quantum system:

[0075] A quantum behavior simulation model is constructed based on the physical behavior of the PUF response under the current environment (such as temperature, electromagnetic interference, voltage and other parameters). The model is based on the Schrödinger equation in quantum mechanics and describes the evolution of the PUF response in the quantum state.

[0076] With the state vector Indicates the PUF response at time The quantum state under the initial state It is determined by the characteristics of the PUF physical structure, and its evolution is determined by environmental factors.

[0077] Taking environmental parameters as external input variables, environmental parameters will affect the quantum state of PUF response.

[0078] Environmental parameters include temperature, electromagnetic interference intensity, and voltage.

[0079] Introducing environmental parameters into the Hamiltonian of quantum mechanics through coupling terms It is used to simulate the disturbance of the actual environment to the PUF, which can be achieved through the following formula: .

[0080] in, is the Hamiltonian of the system when there is no environmental disturbance; Represents the disturbance term of the current environmental parameters on the system; is the temperature, is the electromagnetic interference intensity, is voltage.

[0081] The above quantum model is simulated by numerical methods (such as solving time-dependent differential equations) to obtain the quantum states of the PUF response at different time points.

[0082] S202: Calculate the decoherence time of the PUF response through quantum decoherence analysis to quantify the PUF stability:

[0083] Quantum decoherence refers to the process in which a quantum state gradually loses coherence due to environmental interference and eventually transforms into a classical state.

[0084] Using the density matrix represents the quantum state of the PUF system, where It is calculated based on the quantum state of the PUF response. Environmental interference will cause the non-diagonal elements of the density matrix to decay, forming a decoherence process.

[0085] Density Matrix The expression is: ;in, yes The conjugate transpose (sometimes called the Hermitian conjugate) of .

[0086] The decoherence time of the PUF response is calculated by tracking the decay rate of the off-diagonal elements of the density matrix The specific calculation method is as follows: ;in, is the decoherence rate, which is the exponential coefficient of the decay of the non-diagonal elements of the density matrix over time.

[0087] Decoherence time The longer the decoherence time is, the more stable the PUF response is in the current environment. On the contrary, a shorter decoherence time means that the environment has a greater impact on the PUF response.

[0088] S203: Match the decoherence analysis results with the current environment data to evaluate the impact of the environment on the PUF response:

[0089] The environmental parameters collected in real time are preprocessed, including noise removal, data curve smoothing, etc., to make the environmental parameters suitable for subsequent analysis.

[0090] Decoherence time The environmental impact model is constructed by correlation analysis with the current environmental parameters. The environmental impact model represents the impact of the current environment on the stability of PUF response. The correlation model can be defined as: ; Among them, the function It represents the nonlinear relationship between the decoherence time and various environmental parameters, which is obtained by fitting the experimental data.

[0091] According to the fitting function , input the real-time environmental parameters into the model to predict the impact of the environment on the PUF response. By analyzing the model output results, it is determined whether the environment has an unstable impact on the PUF response.

[0092] S204: Based on the decoherence time and the environment matching result, a decoherence stability judgment value is calculated for continuous monitoring of the PUF state:

[0093] Based on the decoherence time Match the results with the environmental parameters and calculate the decoherence stability judgment value Used to monitor the stability of PUF response in real time. The decoherence stability judgment value is determined by the decoherence time and the matching degree of environmental parameters, and its expression is: .

[0094] and Decoherence time The weight coefficient of the function matching the environment can be adjusted through experiments.

[0095] It is the environment matching function, which indicates the influence of the environment on the stability of PUF.

[0096] in, is based on Specifically, By fitting the experimental data, a nonlinear relationship between environmental parameters such as temperature, electromagnetic interference and voltage and the PUF response stability (decoherence time) was established. Used to predict the PUF response characteristics under different environmental conditions. That is, the matching value calculated by using this function is used to evaluate the impact of the environment on the stability of PUF in real time.

[0097] Setting the stability threshold .when When , the PUF is determined to be stable in the current environment; when , the PUF is determined to be unstable in the current environment and an alarm is issued, indicating that the PUF response may be unstable.

[0098] By periodically calculating the decoherence stability judgment value , continuously monitor the status of the PUF response. Once it is found If the value falls below a preset threshold, the corresponding response mechanism is triggered, such as stopping key generation or performing error correction.

[0099] S3 is specifically:

[0100] Set the preset environmental threshold. The preset environmental threshold is the environmental range allowed for the hardware device to operate stably, including the temperature threshold range. arrive , Voltage threshold range arrive And the electromagnetic interference intensity threshold arrive . The environmental parameters collected in real time , , Compare with the preset environmental thresholds to determine whether they are within an acceptable stability range.

[0101] if , the temperature is considered to be in a stable state; otherwise, the temperature is considered to be out of the acceptable range and may affect the stability of the system.

[0102] if , the voltage is considered to be in a stable state; otherwise, the voltage is abnormal, which may have an adverse effect on the PUF response.

[0103] if , the electromagnetic interference level is considered to be within an acceptable range; otherwise, the interference intensity is too large and may cause the PUF response to be unstable.

[0104] After independent judgment, when all environmental parameters meet their corresponding threshold conditions at the same time, the current environment of the hardware device is determined to be within the acceptable stability range. , , ) exceeds its corresponding threshold range, it is determined that the current environment of the hardware device is not within the acceptable stability range, the current environment is unstable, and may affect the reliability of the PUF response.

[0105] S4 specifically includes:

[0106] S401: De-noising and standardizing the collected PUF response signal:

[0107] Since the PUF response signal may be interfered by noise, denoising is first performed. We use a denoising method based on wavelet transform to decompose the signal into multiple frequency bands and remove irrelevant high-frequency noise. This process can separate noise and useful signals, thereby ensuring the accuracy of self-similarity analysis.

[0108] In order to ensure the consistency of signals at different time scales, the PUF response signal must be standardized. The standardization formula is as follows: ;in, represents the standardized PUF response signal, is the first value of the original PUF response signal collected data points, is the collected original PUF response signal The mean of is the collected original PUF response signal The standard deviation of .

[0109] After standardization, the signal has a mean of zero and a standard deviation of one, which helps eliminate amplitude differences between different data points and ensures consistency in subsequent analysis.

[0110] S402: Segmentally sample the PUF response signal at preset time intervals to obtain signal segments at multiple time scales:

[0111] When performing self-similarity analysis, the signal needs to be segmented at different time scales. We choose the appropriate time interval based on the sampling frequency , and set multiple time scales ,in Indicates time scale (e.g. 1 ms, 10 ms, 100 ms, etc.).

[0112] The standardized PUF response signal By time interval Segmentation to obtain The formula for segmented sampling is: ;in, It is The signal fragments at each time scale are It is time scale, is the time interval of segment sampling.

[0113] Through the segmented sampling method, the changes in the PUF response signal can be observed on multiple time scales, providing data support for subsequent self-similarity analysis.

[0114] S403: Use the Hurst exponent to construct a self-similarity analysis model for signals to quantify the similarity of signals at different scales:

[0115] The Hurst index is an indicator to measure the self-similarity of a time series. By calculating the Hurst index, we can determine the self-similarity of a signal at different time scales. Generally speaking, the value of the Hurst index is between 0 and 1:

[0116] Indicates that the signal is completely random.

[0117] It means that the signal has positive self-similarity (i.e., has long-term dependence).

[0118] It means that the signal has negative self-similarity (i.e., anti-persistence).

[0119] In order to calculate the Hurst index, the rescaled range analysis (R / S analysis) is used, and the formula is as follows: ;in, It is on the time scale The range of the upper signal (i.e. the difference between the maximum and minimum values ​​of the signal segment); is the standard deviation of the signal segment, indicating the degree of fluctuation of the signal on this time scale; is a proportionality constant, which is related to the amplitude of the specific signal; is the Hurst exponent.

[0120] By calculating the R / S ratio at different time scales and plotting The Hurst index can be obtained by fitting the slope of the curve with the logarithmic graph of the R / S ratio.

[0121] S404: Based on the self-similarity analysis model, the self-similarity parameter is calculated to measure the scale-invariant property of the signal:

[0122] Based on the Hurst index in S403, calculate the self-similarity parameter , which is used to measure the overall scale-invariant characteristics of the signal. The formula is as follows: ;in, is the self-similarity parameter, which is used to represent the overall similarity of the signal at all time scales; is the total number of time scales; It is in Time scale The Hurst exponent calculated on .

[0123] The closer the self-similarity parameter is to 1, the stronger the self-similarity of the signal is on different time scales; if the self-similarity parameter is lower, the weaker the self-similarity of the signal is.

[0124] S405: Evaluate the stability and consistency of the PUF response signal in the current environment by comparing the calculated self-similarity parameters:

[0125] In order to determine whether the PUF response signal is stable in the current environment, a stability threshold of the self-similarity parameter is preset. ; If the calculated self-similarity parameter The following conditions are met: ; It is determined that the PUF response signal has good stability and consistency in the current environment and is suitable for generating encryption keys.

[0126] if , it is determined that the PUF response signal is not stable and consistent in the current environment and may be affected by environmental changes. In this case, further measures are needed, such as re-collecting the signal, adjusting environmental parameters, or applying an error correction algorithm to correct the signal.

[0127] In step S2, quantum behavior simulation and quantum decoherence analysis are integrated to evaluate the stability of PUF response in the initial stage, which not only improves the accuracy of the evaluation, but also enables the entire system to identify the potential impact of environmental factors on PUF performance in the first place. In step S4, the Hurst index is introduced to construct a self-similarity model to perform microscopic stability analysis on PUF response, which can analyze the self-similarity of the signal at a more detailed level and provide a scientific basis for judging the long-term stability of the signal. This continuous evaluation strategy from macro to micro not only optimizes the entire PUF response processing flow, but also greatly enhances the overall performance and security of the information security storage method.

[0128] Generate an encryption key using the PUF response, specifically:

[0129] According to the PUF response signal generated in step S1, its digital output is extracted. Generally, the PUF response is highly random and unpredictable.

[0130] Taking the PUF response as input, a fixed-length encryption key is generated using a predetermined key generation algorithm such as SHA-256 or Linear Feedback Shift Register (LFSR).

[0131] The generated encryption key will be temporarily stored in a hardware security module (such as a TPM) for subsequent encryption operations. At this point, the key can be used to protect sensitive information.

[0132] Apply a predetermined error correction algorithm to the PUF response to correct the initial encryption key, specifically:

[0133] First, the PUF response is checked for integrity to identify error bits or deviations caused by environmental changes or PUF instability. Common methods include repeatedly reading the PUF response and calculating the difference, or detecting abnormal bits through parity checks.

[0134] Once a deviation in the PUF response is detected, it is corrected using a predetermined error correction algorithm. Common error correction algorithms include:

[0135] Low-density parity-check code (LDPC): Corrects error bits through an iterative algorithm, especially suitable for signals with strong randomness.

[0136] Turbo codes: Used to efficiently correct a large number of error bits.

[0137] Hamming code: Suitable for correcting small errors.

[0138] By correcting the original PUF response, the generated encryption key is ensured to be error-free.

[0139] After applying the error correction algorithm, the generated correction key needs to be verified for integrity. By comparing the correction key with a known reference key (such as a pre-stored initial key), it is ensured that the corrected key is correct and safe to use. If the verification passes, the correction key is stored and used; otherwise, an alarm is issued and the use is refused.

[0140] Example 2

[0141] The difference between Embodiment 2 of the present invention and Embodiment 1 is that this embodiment introduces an electronic information security storage system.

[0142] Figure 2 A structural schematic diagram of an electronic information security storage system of the present invention is given, which includes a key generation module, a stability analysis module, an environment monitoring module, a signal analysis module and a key decision module.

[0143] Key generation module: Generates PUF response from hardware devices under controlled environmental conditions to obtain initial encryption keys.

[0144] Stability analysis module: Through quantum decoherence analysis based on quantum behavior simulation, it continuously determines whether the PUF is stable in the current environment.

[0145] Environmental monitoring module: collects environmental data around the hardware device in real time; determines whether the current environment of the hardware device is within an acceptable and stable range by comparing the environmental data with the preset environmental threshold.

[0146] Signal analysis module: Through segmented sampling of the PUF response signal, a self-similarity model is constructed based on the Hurst exponent, and the self-similarity parameters are calculated to evaluate the stability and consistency of the PUF response signal.

[0147] Key decision module: When the PUF is stable in the current environment, the current environment of the hardware device is within an acceptable stability range, and the PUF response signal has good stability and consistency in the current environment, the PUF response is used to generate an encryption key; otherwise, a predetermined error correction algorithm is applied to the PUF response to correct the initial encryption key.

[0148] 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 and thresholds in the formula are set by technicians in this field according to actual conditions.

[0149] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may 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 may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or may be transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may 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 may 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 may be a solid-state hard disk.

[0150] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein 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 be beyond the scope of this application.

[0151] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0152] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0153] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0154] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0155] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0156] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present 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. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0157] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for secure storage of electronic information, characterized in that: The steps include: S1: Generate PUF response from hardware device under controlled environmental conditions to obtain initial encryption key; S2: Through quantum decoherence analysis based on quantum behavior simulation, continuously determine whether the PUF is stable in the current environment; S3: Collect environmental data around the hardware device in real time; determine whether the current environment of the hardware device is within an acceptable and stable range by comparing the environmental data with the preset environmental threshold; S4: By performing segmented sampling on the PUF response signal, a self-similarity model is constructed based on the Hurst exponent, and the self-similarity parameter is calculated to evaluate the stability and consistency of the PUF response signal; S5: When the PUF is stable in the current environment, the current environment of the hardware device is within an acceptable stability range, and the PUF response signal has good stability and consistency in the current environment, the PUF response is used to generate an encryption key; otherwise, a predetermined error correction algorithm is applied to the PUF response to correct the initial encryption key; S2 specifically includes: S201: Construct a quantum behavior simulation model based on current environmental parameters to simulate the performance of PUF response in the quantum system; S202: Calculate the decoherence time of the PUF response by quantum decoherence analysis to quantify the PUF stability; S203: Match the decoherence analysis result with the current environment data to evaluate the impact of the environment on the PUF response; S204: Calculate the decoherence stability judgment value based on the decoherence time and the environment matching result, and continuously monitor the PUF state; S4 specifically includes: S401: performing denoising and standardization processing on the collected PUF response signal; S402: Segmentally sample the PUF response signal at preset time intervals to obtain signal segments at multiple time scales; S403: Use the Hurst exponent to construct a self-similarity analysis model for signals to quantify the similarity of signals at different scales; S404: Based on the self-similarity analysis model, a self-similarity parameter is calculated to measure the scale-invariant characteristic of the signal; S405: Evaluate the stability and consistency of the PUF response signal in the current environment by comparing the calculated self-similarity parameters.

2. A method for securely storing electronic information according to claim 1, characterized in that: S1 specifically includes: S101: Start the hardware device in a controlled environment; S102: Triggering the PUF module through a control signal to prepare to generate a unique physical response; S103: Using an acquisition circuit to read and digitally process the physical response signal output by the PUF module; S104: Based on the collected PUF response signal, a unique initial encryption key is generated by a predetermined algorithm.

3. A method for securely storing electronic information according to claim 2, characterized in that: S204 is specifically: based on the decoherence time t d Match the results with the environmental parameters and calculate the decoherence stability judgment value S p , its expression is: S p =α·t d +β·Match(T e , B e , V e ), where α and β are the decoherence time t d and the weight coefficient of the environment matching function; Match(T e , B e , V e ) is the environment matching function; T e is temperature, B e is the electromagnetic interference intensity, V e is the voltage; Set the stability threshold S th ; When S p ≥S th When S p <S th , then it is determined that PUF is unstable in the current environment.

4. A method for securely storing electronic information according to claim 3, characterized in that: S3 is specifically: Set a preset environmental threshold and compare the environmental parameters collected in real time with the preset environmental threshold respectively; When all environmental parameters simultaneously meet their corresponding threshold conditions, it is determined that the current environment of the hardware device is within the acceptable stable range; otherwise, it is determined that the current environment of the hardware device is not within the acceptable stable range; Among them, environmental parameters include temperature, electromagnetic interference intensity and voltage.

5. A method for securely storing electronic information according to claim 4, characterized in that: The Hurst index is calculated using rescaled range analysis, and the formula is as follows: Among them, R(T k ) is in the time scale T k The upper signal range, S(T k ) is the standard deviation of the signal segment, C is the proportionality constant, which is related to the amplitude of the specific signal; H is the Hurst exponent; Calculate the self-similarity parameter S sim , the formula is as follows: Among them, S sim is the self-similarity parameter, M is the total number of time scales, H k is at the kth time scale T k The Hurst index calculated above, k is the number of the time scale; Preset the stability threshold S of the self-similarity parameter th ; if S sim >S th ; It is determined that the PUF response signal has good stability and consistency in the current environment; If S min <S th , it is determined that the PUF response signal is not stable and consistent in the current environment.

6. An electronic information security storage system, used to implement an electronic information security storage method according to any one of claims 1 to 5, characterized in that: It includes a key generation module, a stability analysis module, an environment monitoring module, a signal analysis module and a key decision module; Key generation module: Generates PUF response from hardware devices under controlled environmental conditions to obtain initial encryption keys; Stability analysis module: Through quantum decoherence analysis based on quantum behavior simulation, it continuously determines whether the PUF is stable in the current environment; Environmental monitoring module: collects environmental data around hardware devices in real time; determines whether the current environment of the hardware device is within an acceptable and stable range by comparing the environmental data with the preset environmental threshold; Signal analysis module: Through segmented sampling of PUF response signals, a self-similarity model is constructed based on the Hurst exponent, and self-similarity parameters are calculated to evaluate the stability and consistency of PUF response signals; Key decision module: When the PUF is stable in the current environment, the current environment of the hardware device is within an acceptable stability range, and the PUF response signal has good stability and consistency in the current environment, the PUF response is used to generate an encryption key; otherwise, a predetermined error correction algorithm is applied to the PUF response to correct the initial encryption key.

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