Quantum dot laser-based true random number generation method and system

Abstract

The application provides a quantum dot laser-based true random number generation method, comprising the following steps: simulating a chaotic laser signal generated by a quantum dot laser; setting a sampling step h to extract light intensity data of the chaotic laser signal, smoothing the signal by using a Savitzky-Golay filter to obtain an original light intensity data sequence; performing differential derivation on the original light intensity data sequence to generate a preliminary extreme value output sequence; performing symmetric quantization on the extreme value output sequence in a maximum value descending order sorting and a minimum value ascending order sorting manner to generate a preliminary binary quantization sequence; enhancing randomness of the preliminary binary quantization sequence; performing NIST randomness testing on a final high-quality random number sequence to output a high-quality true random number sequence meeting a testing quality requirement. The application has the beneficial effects that the true random number generator can realize the combination of high speed, high stability, small size and optical applicability.

Description

Technical Field

[0001] This invention relates to the field of semiconductor optoelectronics technology, specifically to a method and system for generating true random numbers based on quantum dot lasers. Background Technology

[0002] A random number generator is a device that generates a stream of data, where each bit is unpredictable and random. Random number generators can be broadly classified into two categories based on their working principle: pseudo-random number generators (PRNGs) and true random number generators (TRNGs). PRNGs generate random numbers using a deterministic algorithm; these numbers are not truly random but appear random. They pass all available statistical tests for randomness. Because these numbers are repeatable, they are pseudo-random. Many compilers provide built-in PRNGs, such as C / C++'s `rand()` and Object Pascal's `random()`. TRNGs utilize physical phenomena such as thermal noise, chaotic circuits, and cosmic rays to generate unpredictable random numbers.

[0003] Random numbers play a crucial role in cybersecurity, defense, and other fields, primarily used in encryption technologies and security protocols where data security is paramount. Pseudo-random numbers, due to their predictability, cannot meet the data security requirements of critical sectors, while existing true random number generators also have numerous drawbacks. Currently, common true random number generators mainly fall into two categories: radioactive decay-based random number generators and photon detector-based random number generators. Radioactive decay-based random number generators use electronic devices as the source of chaos, resulting in poor stability and significant susceptibility to external interference; they also have stringent operating conditions, with considerable limitations imposed by environmental temperature and humidity, limiting their applicability; and they are costly and generate random numbers slowly. Photon detector-based random number generators, such as quantum random number generators, generate true random numbers at speeds up to 150Gbps, but their large size prevents them from being embedded in systems, requiring complex installation and design for practical application, and occupies considerable space. In summary, current true random number generators cannot satisfy the requirements of speed, cost, and size, making them insufficient to meet user needs. Summary of the Invention

[0004] To address the problems in existing technologies, this invention provides a method and system for generating true random numbers based on quantum dot lasers. By using a quantum dot laser as a chaotic source and adding a plane mirror at an appropriate position outside the laser, a chaotic laser signal is generated using an optical feedback method. This method is highly reliable, not easily affected by the environment, and is very suitable as a random source for generating true random numbers. The true random number generation rate is greater than 100Gbps, achieving a combination of high speed, high stability, small size, and optical applicability for true random number generators. This fills the gap in current related technologies and solves the problems of poor stability, large size, and complex installation and operation of existing true random number generators.

[0005] This invention provides a true random number generation method based on a quantum dot laser, comprising:

[0006] Step 1: Initialize the optical feedback system, simulate the generation of chaotic laser signals produced by the quantum dot laser, and extract random light intensity data from the chaotic laser signals as the initial random source. The optical feedback system includes a quantum dot laser and a plane mirror.

[0007] Step 2: Chaotic laser signal acquisition and preprocessing. By setting the sampling step size h as a hyperparameter, the light intensity data of the chaotic laser signal is extracted. The signal is smoothed by using a Savitzky-Golay filter to remove high-frequency noise and obtain a relatively pure original light intensity data sequence.

[0008] Step 3, Feature extraction and differential calculation: Perform differential calculation on the filtered original light intensity data sequence. Based on the time interval between adjacent extreme values ​​and the rate of change of the derivative of the extreme values, extract and screen the extreme value points that meet the threshold conditions to generate a preliminary extreme value output sequence.

[0009] Step 4: Data grouping, sorting, and symmetric quantization. The extreme value output sequence is grouped according to a set size, and symmetric quantization is performed by sorting the maximum value in descending order and the minimum value in ascending order. After the quantization process, the quantized maximum value sequence and the minimum value sequence are cross-connected to generate a preliminary binary quantized sequence.

[0010] Step 5, random enhancement processing: The randomness of the initial binary quantized sequence is enhanced by one-complement insertion, improved Von Neumann randomization algorithm and SHA-256 hash processing to obtain the final high-quality true random number sequence. The improved Von Neumann randomization algorithm is to perform improved Von Neumann randomization processing on the initial binary quantized sequence, filter and merge every three numbers into a new sequence, and then divide it into sub-blocks of length 256, and perform SHA-256 hash processing on each of them.

[0011] Step 6, Random Number Verification and Output: Perform NIST randomness testing on the final high-quality random number sequence, and output the high-quality true random number sequence that meets the NIST randomness test quality requirements.

[0012] In a further improvement to the present invention, in step 1, the optical feedback system includes a quantum dot laser and a plane mirror. The plane mirror is disposed outside the quantum dot laser and is adapted to the quantum dot laser. The plane mirror is capable of generating chaotic laser signals with the quantum dot laser.

[0013] In a further improvement to the present invention, in step 1, both the quantum dot laser and the planar mirror can be integrated and fabricated on a chip.

[0014] The present invention is further improved in that, in step 3, when screening out extreme points that meet the threshold conditions, the extreme points with smaller time intervals and larger rate of change of derivatives are preferentially eliminated.

[0015] The present invention is further improved in that, in step 5, the inverse code insertion includes mapping the initial binary quantized sequence after symmetric quantization to the insertion position according to a preset ratio, and inserting the inverse code of the initial binary quantized sequence into the initial binary quantized sequence according to the predetermined insertion position, thereby generating a new sequence and increasing the randomness and uniformity of data distribution.

[0016] The present invention is further improved in step 5 by performing von Neumann encoding on the new sequence generated by the inverse code insertion in groups of three numbers to remove correlation, and dividing the processed data into 256-bit sub-blocks for SHA-256 hashing. All hash result sub-blocks are merged and then the inverse code insertion is performed again to generate the final high-quality true random number sequence.

[0017] The present invention is further improved in that, in step 6, the final high-quality true random number sequence generation rate exceeds 100Gbps.

[0018] The present invention also provides a system for the above-described true random number generation method based on quantum dot lasers, comprising:

[0019] The chaotic laser generation module uses a chaotic laser signal with high entropy characteristics generated by a quantum dot laser as the initial random source for true random numbers.

[0020] The data receiving and preprocessing module acquires the light intensity data of the chaotic laser signal and smooths the signal through a Savitzky-Golay filter to obtain a raw light intensity data sequence with very little noise.

[0021] The differential differentiation module performs differential differentiation on the filtered original light intensity data sequence. When filtering extreme values, it judges based on the time interval between adjacent extreme values ​​and the rate of change of the derivative of the extreme values, discarding extreme values ​​with too small a time interval between adjacent values ​​or too large a rate of change of the derivative, and generating a preliminary extreme value output sequence.

[0022] The symmetric quantization module groups the selected extreme value data according to the input group size and quantization bit depth. It then sorts the maxima in descending order and the minima in ascending order using the symmetric quantization method, quantizes them into a 01 sequence, and performs cross-connection to generate a preliminary binary quantized sequence.

[0023] The inverse code insertion module first determines whether each bit is 0 or 1, performs code inversion on the preliminary binary quantized sequence obtained after symmetric quantization and cross-connection, generates the corresponding inverse code sequence, then maps the preliminary binary quantized sequence to the insertion position according to the ratio, inserts the corresponding inverse code sequence random number into the specified insertion position of the preliminary binary quantized sequence, and finally merges them to generate the complete insertion sequence.

[0024] The random enhancement module performs improved Von Neumann randomization on the input random sequence entering this module. It filters and merges every three numbers into a new sequence, then divides it into sub-blocks of length 256, and performs SHA-256 hashing on each of them.

[0025] The verification and output module performs NIST randomness testing on the final high-quality random number sequence and outputs a high-quality true random number sequence that meets the NIST randomness test quality requirements.

[0026] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention provides a true random number generation method and system based on quantum dot lasers. By using a quantum dot laser as a chaotic source and adding a plane mirror at an appropriate position outside the laser, a chaotic laser signal is generated using an optical feedback method. Since the chaotic laser signal is a physical chaotic source, its characteristic values ​​such as light intensity and frequency are all random values. Furthermore, since this chaotic source is generated based on a quantum dot laser, the quantum dot laser itself has a stable structure. Although the generated chaotic laser signal becomes chaotic after being reflected by the mirror, the properties of the chaotic laser are still very reliable and not easily affected by the environment. It is very suitable for use as a random source for generating true random numbers, with a generation rate greater than 100Gbps. Moreover, the quantum dot laser has high entropy and high stability characteristics, and the properties of the generated chaotic laser change rapidly, making it a good physical chaotic source. This invention achieves a combination of high speed, high stability, small size, and optical applicability in a true random number generator, filling the gap in current related technologies and solving the problems of poor stability, large size, and complex installation and operation of existing true random number generators. Attached Figure Description

[0027] To more clearly illustrate the solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0028] Figure 1 This is a flowchart of the true random number generation method based on quantum dot laser of the present invention;

[0029] Figure 2 This is a flowchart of the present invention for performing differential calculation on the filtered original light intensity data sequence;

[0030] Figure 3 This is a flowchart of the data grouping, sorting, and symmetric quantization process of the present invention;

[0031] Figure 4 This is a flowchart of the inverse code insertion process in the random enhancement process of the present invention;

[0032] Figure 5 This is a flowchart of the random enhancement process of the present invention;

[0033] Figure 6 This is a schematic diagram of the extreme values ​​obtained by differential differentiation of the filtered original light intensity data sequence according to the present invention. Detailed Implementation

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having” and any variations thereof in the specification, claims and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0035] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0036] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0037] like Figures 1-6As shown, the present invention provides a true random number generation method based on a quantum dot laser, comprising:

[0038] Step 1: Initialize the optical feedback system, simulate the generation of chaotic laser signals from the quantum dot laser, and extract random light intensity data from the chaotic laser signals as the initial random source. The optical feedback system includes a quantum dot laser and a plane mirror. The plane mirror is placed outside the quantum dot laser and is adapted to the quantum dot laser. The plane mirror can generate chaotic laser signals with the quantum dot laser. Both the quantum dot laser and the plane mirror can be integrated and fabricated on a chip, and can be fabricated on the same chip. In this embodiment, because the quantum dot laser is only on the nanometer scale and the discrete distribution of the quantum dot structure has a high tolerance for defects in epitaxial growth on silicon, it can effectively deflect or clamp defects to prevent the formation of loops. At the same time, it can locate the charge carriers to prevent lateral diffusion or nonradiative recombination, thereby significantly reducing the impact of dislocation defects on the laser characteristics. Therefore, it can be integrated on a chip, and the planar mirror can also be integrated and fabricated on the chip, which greatly improves the system integration and significantly reduces the size of existing devices. Furthermore, due to the three-dimensional quantum confinement effect of the quantum dot laser, it is easy to generate a chaotic state under optical feedback. At the same time, its low spontaneous emission noise is conducive to generating high-quality chaotic signals. In addition, the nonlinear dynamic characteristics of the charge carriers of the quantum dot laser help maintain chaotic behavior, and its strong adaptability to environmental changes ensures the stable output of chaotic signals, which is conducive to the stable and high-quality generation of true random numbers.

[0039] Step 2: Chaotic laser signal acquisition and preprocessing. By setting the sampling step size h as a hyperparameter, the intensity data of the chaotic laser signal is extracted. A Savitzky-Golay filter is used to smooth the signal, removing high-frequency noise to obtain a relatively pure original intensity data sequence. The Savitzky-Golay filter (often abbreviated as SG filter) is widely used for data stream smoothing and noise reduction. It is a filtering method based on local polynomial least squares fitting in the time domain. The biggest advantage of this filter is that it can ensure the shape and width of the signal remain unchanged while filtering out noise. In this embodiment, using the Savitzky-Golay filter to remove high-frequency noise yields a relatively pure original intensity data sequence. Since the chaotic laser signal is a physical chaotic source, its intensity, frequency, and other characteristic values ​​are all random values. Furthermore, this chaotic source is generated by a laser, which has a stable structure. Although the generated laser becomes chaotic after being reflected by a mirror, the properties of the chaotic laser signal are still very reliable and not easily affected by the environment, making it very suitable as a random source for generating true random numbers.

[0040] Step 3, Feature extraction and differential calculation: Differential calculation is performed on the filtered original light intensity data sequence. Based on the time interval between adjacent extreme values ​​and the rate of change of the derivative of the extreme values, extreme points that meet the threshold conditions are extracted and screened to generate a preliminary extreme value output sequence. When screening extreme points that meet the threshold conditions, extreme points with smaller time intervals and larger rate of change of derivatives are eliminated first.

[0041] Step 4: Data grouping, sorting, and symmetric quantization. The extreme value output sequence is grouped according to a set size, and symmetric quantization is performed by sorting the maximum value in descending order and the minimum value in ascending order. After the quantization process, the quantized maximum value sequence and the minimum value sequence are cross-connected to generate a preliminary binary quantized sequence.

[0042] Step 5, Random Enhancement Process: The initial binary quantized sequence is enhanced with randomness through inverse code insertion, an improved Von Neumann randomization algorithm, and SHA-256 hashing to obtain a final high-quality true random number sequence. The improved Von Neumann randomization algorithm performs this process on the initial binary quantized sequence, merging groups of three numbers into a new sequence, which is then divided into 256-bit sub-blocks and hashed sequentially using SHA-256. Inverse code insertion maps the symmetrically quantized initial binary quantized sequence to the insertion position according to a preset ratio, inserting the inverse code of the initial binary quantized sequence into the predetermined position to generate a new sequence, increasing the randomness and uniformity of the data distribution. The new sequence generated by inverse code insertion is then von Neumann encoded in groups of three numbers to remove correlation, and the processed data is divided into 256-bit sub-blocks for SHA-256 hashing. All hash result sub-blocks are merged and then subjected to another inverse code insertion to generate the final high-quality true random number sequence.

[0043] Step 6: Random number verification and output. The final high-quality random number sequence is subjected to NIST randomness testing. A high-quality true random number sequence that meets the NIST randomness test quality requirements is output. The final high-quality true random number sequence generation rate exceeds 100Gbps. In this embodiment, the operator can acquire and process the quantum dot laser output signal on the PC control module to generate a high-quality true random number sequence. The true random number sequence generation rate exceeds 100Gbps, which, although slightly slower than a quantum random number generator, can cover all applications requiring high randomness properties. Furthermore, its small size makes it suitable for integrated chip design. Table 1 shows the NIST statistical test results of the high-quality true random number sequence in this embodiment.

[0044] Data testing p-value By proportion result frequency 0.236810 1 success block frequency 0.115387 1 success Summation 0.289667 1 success Tour 0.455937 1 success Longest run within a block 0.779188 1 success Rank of a binary matrix 0.739918 0.97 success Discrete Fourier Transform 0.924076 1 success Non-overlapping module matching test 0.224821 0.984 success Overlapping module matching check 0.262249 0.99 success General Statistics 0.350485 1 success Approximate Entropy 0.350485 1 success Random walk 0.162606 0.948 success Random walk state frequency 0.275709 0.935 success sequence 0.564815 0.99 success linear complexity 0.289667 0.97 success

[0045] Table 1. Statistical test results of high-quality true random number sequences from NIST

[0046] like Figures 1-6 As shown, the present invention also provides a system for the above-described true random number generation method based on quantum dot lasers, comprising:

[0047] The chaotic laser generation module uses a chaotic laser signal with high entropy characteristics generated by a quantum dot laser as the initial random source for true random numbers.

[0048] The data receiving and preprocessing module acquires the light intensity data of the chaotic laser signal and smooths the signal through a Savitzky-Golay filter to obtain a raw light intensity data sequence with very little noise.

[0049] The differential differentiation module performs differential differentiation on the filtered original light intensity data sequence. When filtering extreme values, it judges based on the time interval between adjacent extreme values ​​and the rate of change of the derivative of the extreme values, discarding extreme values ​​with too small a time interval between adjacent values ​​or too large a rate of change of the derivative, and generating a preliminary extreme value output sequence.

[0050] The symmetric quantization module groups the selected extreme value data according to the input group size and quantization bit depth. It then sorts the maxima in descending order and the minima in ascending order using the symmetric quantization method, quantizes them into a 01 sequence, and performs cross-connection to generate a preliminary binary quantized sequence.

[0051] The inverse code insertion module first determines whether each bit is 0 or 1, performs code inversion on the preliminary binary quantized sequence obtained after symmetric quantization and cross-connection, generates the corresponding inverse code sequence, then maps the preliminary binary quantized sequence to the insertion position according to the ratio, inserts the corresponding inverse code sequence random number into the specified insertion position of the preliminary binary quantized sequence, and finally merges them to generate the complete insertion sequence.

[0052] The random enhancement module performs improved Von Neumann randomization on the input random sequence entering this module. It filters and merges every three numbers into a new sequence, then divides it into sub-blocks of length 256, and performs SHA-256 hashing on each of them.

[0053] The verification and output module performs NIST randomness testing on the final high-quality random number sequence and outputs a high-quality true random number sequence that meets the NIST randomness test quality requirements. In this embodiment, the key feature of this system is that through multi-stage processing (such as filtering, differential differentiation, symmetric quantization, inverse code insertion, improved von Neumann coding, and hashing), it generates high-entropy, uniformly distributed true random number sequences without relying on external environments, making it suitable for applications requiring high security and high stability.

[0054] As can be seen from the above, this invention provides a true random number generation method and system based on a quantum dot laser. By using a quantum dot laser as a chaotic source and adding a plane mirror at an appropriate position outside the laser, a chaotic laser signal is generated using an optical feedback method. Since the chaotic laser signal is a physical chaotic source, its characteristic values ​​such as light intensity and frequency are all random values. Furthermore, since this chaotic source is generated based on a quantum dot laser, and the quantum dot laser itself has a stable structure, although the generated chaotic laser signal becomes chaotic after being reflected by the mirror, the properties of the chaotic laser are still very reliable and not easily affected by the environment. It is very suitable for use as a random source for generating true random numbers, with a generation rate greater than 100Gbps. Moreover, the quantum dot laser has high entropy and high stability characteristics, and the properties of the generated chaotic laser change rapidly, making it a good physical chaotic source. This invention achieves a combination of high speed, high stability, small size, and optical applicability in a true random number generator, filling the gap in current related technologies and solving the problems of poor stability, large size, and complex installation and operation of existing true random number generators.

[0055] The specific embodiments described above are preferred embodiments of the present invention and are not intended to limit the specific scope of the present invention. The scope of the present invention includes, but is not limited to, these specific embodiments. All equivalent changes made in accordance with the present invention are within the protection scope of the present invention.

Claims

1. A method for generating truly random numbers based on quantum dot lasers, characterized in that, include: Step 1: Initialize the optical feedback system, simulate the generation of chaotic laser signals produced by the quantum dot laser, and extract random light intensity data from the chaotic laser signals as the initial random source. The optical feedback system includes a quantum dot laser and a plane mirror. Step 2: Chaotic laser signal acquisition and preprocessing. By setting the sampling step size h as a hyperparameter, the light intensity data of the chaotic laser signal is extracted. The signal is smoothed by using a Savitzky-Golay filter to remove high-frequency noise and obtain a relatively pure original light intensity data sequence. Step 3, Feature extraction and differential calculation: Perform differential calculation on the filtered original light intensity data sequence. Based on the time interval between adjacent extreme values ​​and the rate of change of the derivative of the extreme values, extract and screen the extreme value points that meet the threshold conditions to generate a preliminary extreme value output sequence. Step 4: Data grouping, sorting, and symmetric quantization. The extreme value output sequence is grouped according to a set size, and symmetric quantization is performed by sorting the maximum value in descending order and the minimum value in ascending order. After the quantization process, the quantized maximum value sequence and the minimum value sequence are cross-connected to generate a preliminary binary quantized sequence. Step 5, random enhancement processing: The randomness of the initial binary quantized sequence is enhanced by one-complement insertion, improved Von Neumann randomization algorithm and SHA-256 hash processing to obtain the final high-quality true random number sequence. The improved Von Neumann randomization algorithm is to perform improved Von Neumann randomization processing on the initial binary quantized sequence, filter and merge every three numbers into a new sequence, and then divide it into sub-blocks of length 256, and perform SHA-256 hash processing on each of them. Step 6, Random Number Verification and Output: Perform NIST randomness testing on the final high-quality random number sequence, and output the high-quality true random number sequence that meets the NIST randomness test quality requirements.

2. The true random number generation method based on quantum dot laser according to claim 1, characterized in that: In step 1, the optical feedback system includes a quantum dot laser and a plane mirror. The plane mirror is disposed outside the quantum dot laser and is adapted to the quantum dot laser. The plane mirror is capable of generating chaotic laser signals with the quantum dot laser.

3. The true random number generation method based on quantum dot laser according to claim 2, characterized in that: In step 1, both the quantum dot laser and the planar mirror can be integrated and fabricated on a chip.

4. The true random number generation method based on quantum dot laser according to claim 3, characterized in that: In step 3, when selecting extreme points that meet the threshold conditions, extreme points with smaller time intervals and larger rates of change of derivatives are preferentially eliminated.

5. The true random number generation method based on quantum dot laser according to claim 4, characterized in that: In step 5, the inverse code insertion includes mapping the initial binary quantized sequence after symmetric quantization to the insertion position according to a preset ratio, and inserting the inverse code of the initial binary quantized sequence into the initial binary quantized sequence at the predetermined insertion position, thereby generating a new sequence and increasing the randomness and uniformity of data distribution.

6. The true random number generation method based on quantum dot laser according to claim 5, characterized in that: In step 5, the new sequence generated by the inverse code insertion is von Neumann encoded in groups of three to remove correlations. The processed data is then divided into 256-bit sub-blocks and subjected to SHA-256 hashing. All hash result sub-blocks are merged and then subjected to another inverse code insertion to generate the final high-quality true random number sequence.

7. The true random number generation method based on quantum dot laser according to claim 6, characterized in that: In step 6, the final high-quality true random number sequence generation rate exceeds 100Gbps.

8. A system for implementing the true random number generation method based on quantum dot lasers as described in any one of claims 1-7, characterized in that, include: The chaotic laser generation module uses a chaotic laser signal with high entropy characteristics generated by a quantum dot laser as the initial random source for true random numbers. The data receiving and preprocessing module acquires the light intensity data of the chaotic laser signal and smooths the signal through a Savitzky-Golay filter to obtain a raw light intensity data sequence with very little noise. The differential differentiation module performs differential differentiation on the filtered original light intensity data sequence. When filtering extreme values, it judges based on the time interval between adjacent extreme values ​​and the rate of change of the derivative of the extreme values, discarding extreme values ​​with too small a time interval between adjacent values ​​or too large a rate of change of the derivative, and generating a preliminary extreme value output sequence. The symmetric quantization module groups the selected extreme value data according to the input group size and quantization bit depth. It then sorts the maxima in descending order and the minima in ascending order using the symmetric quantization method, quantizes them into a 01 sequence, and performs cross-connection to generate a preliminary binary quantized sequence. The inverse code insertion module first determines whether each bit is 0 or 1, performs code inversion on the preliminary binary quantized sequence obtained after symmetric quantization and cross-connection, generates the corresponding inverse code sequence, then maps the preliminary binary quantized sequence to the insertion position according to the ratio, inserts the corresponding inverse code sequence random number into the specified insertion position of the preliminary binary quantized sequence, and finally merges them to generate the complete insertion sequence. The random enhancement module performs improved Von Neumann randomization on the input random sequence, filters and merges every three numbers into a new sequence, and then divides it into sub-blocks of length 256, performing SHA-256 hash processing on each sub-block. The verification and output module performs NIST randomness testing on the final high-quality random number sequence and outputs a high-quality true random number sequence that meets the NIST randomness test quality requirements.

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