Highly reliable physical random number generation system and method

Abstract

The invention discloses a highly reliable physical random number generation system and method, the system comprises a digital drive module, a chaotic noise acquisition module, a post-processing module, an online detection module, and an output module; the digital drive module generates a digital drive signal and sends it to the chaotic noise acquisition module; the chaotic noise acquisition module comprises a digital-to-analog converter, a plurality of superlattice devices, and a plurality of analog-to-digital converters; the digital-to-analog converter receives the digital drive signal and converts it into an analog waveform, and uses the analog waveform to drive each superlattice device to generate chaotic oscillation; each analog-to-digital converter samples the chaotic oscillation generated by the corresponding superlattice device and outputs an original random sequence; the post-processing module receives the original random sequence to extract randomness, and obtains multiple groups of physical random numbers with sufficient entropy; the online detection module performs bitwise XOR on each group of physical random numbers, and sends them to the output module, and also sends them to the digital drive module for generating digital drive signals. The invention can realize high-speed generation of physical random numbers.

Description

Technical Field

[0001] The present invention relates to the field of information security technology, and in particular to a highly reliable physical random number generation system and method. Background Art

[0002] With the development of modern information technology, information security has gradually received widespread attention. Physical random number generators have become an important part of modern information systems. The security of information systems depends to a large extent on the quality and quantity of random numbers. Especially in the fields of cryptography, confidential communications, information security, etc., which require high quality of random numbers, high-speed, high-quality physical random numbers extracted from physical random phenomena have become valuable resources, and strict requirements have been placed on the quality and reliability of random numbers generated by random number generation systems.

[0003] Under a certain DC bias, the superlattice device can realize current chaotic oscillation, and can be used as a new type of physical unclonable function (PUF). It can produce unpredictable responses under the action of random challenge signals and can be used to generate high-quality physical random numbers. Moreover, the superlattice device is a strong PUF with enough challenge-response pairs that cannot be completely traversed within a limited time. The superlattice device is physically unclonable, that is, the device is made by complex semiconductor processes, and once prepared, it cannot be copied and imitated in terms of electrical properties, which can ensure that each superlattice device has a specific challenge-response relationship.

[0004] In the current practical physical random number generator, the purely electronic implementation is limited by the bandwidth of physical devices and can only achieve a physical random number generator with a relatively low rate. Moreover, in harsh working environments, it is difficult to ensure that the system can produce physical random numbers stably for a long time, which poses a hidden danger to the security of information systems. Summary of the invention

[0005] In view of the above problems, the present invention proposes a highly reliable physical random number generation system and method, which can generate physical random numbers at a high speed.

[0006] In order to achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions:

[0007] In a first aspect, the present invention provides a highly reliable physical random number generation system, comprising: a digital drive module, a chaotic noise acquisition module, a post-processing module, an online detection module, and an output module;

[0008] The digital driving module generates a digital driving signal and sends it to the chaotic noise acquisition module;

[0009] The chaotic noise acquisition module includes a digital-to-analog converter, a plurality of superlattice devices and a plurality of analog-to-digital converters; the digital-to-analog converter receives the digital driving signal and converts it into an analog waveform, and uses the analog waveform to drive each superlattice device to generate chaotic oscillation; each analog-to-digital converter is respectively connected to the corresponding superlattice device, samples the chaotic oscillation generated by the corresponding superlattice device, and outputs an original random sequence;

[0010] The post-processing module receives the original random sequences output by each analog-to-digital converter, and performs randomness extraction respectively to obtain multiple groups of physical random numbers with sufficient entropy;

[0011] The online detection module performs bitwise XOR on each group of physical random numbers and sends the numbers to the output module for use by the application system, and also sends the numbers to the digital drive module for generating digital drive signals.

[0012] Optionally, the digital drive module, post-processing module and online detection module are all made of FPGA chips.

[0013] Optionally, the number of the superlattice device is equal to the number of sampling channels of the analog-to-digital converter.

[0014] Optionally, the online detection module performs real-time detection on randomness indicators of each group of physical random numbers, and issues an alarm signal once a fault is found in a certain path.

[0015] In a second aspect, the present invention provides a highly reliable physical random number generation method, comprising the following steps:

[0016] A digital driving module is used to generate a digital driving signal, and the digital driving signal is sent to a chaotic noise acquisition module, wherein the chaotic noise acquisition module includes a digital-to-analog converter, a plurality of superlattice devices, and a plurality of analog-to-digital converters;

[0017] The digital drive signal is received by the digital-to-analog converter and converted into an analog waveform, and the analog waveform is used to drive each superlattice device to generate chaotic oscillation; each analog-to-digital converter is respectively connected to the corresponding superlattice device, samples the chaotic oscillation generated by the corresponding superlattice device, and outputs an original random sequence;

[0018] The post-processing module is used to receive the original random sequences output by each analog-to-digital converter, and the randomness is extracted respectively to obtain multiple groups of physical random numbers with sufficient entropy;

[0019] The online detection module performs bitwise XOR on each group of physical random numbers and sends them to the output module for use by the application system. At the same time, they are also sent to the digital drive module for generating digital drive signals.

[0020] Optionally, the digital drive module, post-processing module and online detection module are all made of FPGA chips.

[0021] Optionally, the number of the superlattice device is equal to the number of sampling channels of the analog-to-digital converter.

[0022] Optionally, the method further comprises: using an online detection module to perform real-time detection on the randomness index of each group of physical random numbers, and once a fault is found in a certain path, an alarm signal is issued.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] In the present invention, the digital driving module generates a driving signal to each superlattice in the chaotic noise acquisition module, so that it generates an original random sequence and sends it to the post-processing module. The post-processing module extracts randomness from each original random sequence to generate a true random number. After the online detection module passes the test, the random numbers of each channel are bitwise XORed and then output through the output module. At the same time, the output random number is transmitted to the digital driving module to generate a new driving signal. By using the output random number as input to generate a new driving signal, a closed-loop system that continuously outputs random numbers is formed, and the high-reliability generation of physical random numbers is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments and in conjunction with the accompanying drawings, wherein:

[0026] Figure 1 The figure is a schematic diagram of the structure of a highly reliable physical random number generation system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the scope of protection of the present invention.

[0028] The application principle of the present invention is described in detail below in conjunction with the accompanying drawings.

[0029] Example 1

[0030] The embodiment of the present invention provides a highly reliable physical random number generation system, including: a digital drive module, a chaotic noise acquisition module, a post-processing module, an online detection module, and an output module;

[0031] The digital driving module generates a digital driving signal and sends it to the chaotic noise acquisition module;

[0032] The chaotic noise acquisition module includes a digital-to-analog converter (see Figure 1 The DAC in the structure is a plurality of superlattice devices and a plurality of analog-to-digital converters; the digital-to-analog converter receives the digital driving signal and converts it into an analog waveform, and uses the analog waveform to drive each superlattice device to generate chaotic oscillation; each analog-to-digital converter is respectively connected to the corresponding superlattice device, samples the chaotic oscillation generated by the corresponding superlattice device, and outputs an original random sequence;

[0033] The post-processing module receives the original random sequences output by each analog-to-digital converter, and performs randomness extraction respectively to obtain multiple groups of physical random numbers with sufficient entropy;

[0034] The online detection module performs bitwise XOR on each group of physical random numbers and sends the result to the output module for use by the application system, and also sends the result to the digital drive module for generating a digital drive signal. In the embodiment of the present invention, after each group of physical random numbers is outputted through bitwise XOR, the entropy of the random numbers finally outputted will not be worse than that of the original groups of random numbers, so that the quality of the output random numbers is better.

[0035] In a specific implementation of the embodiment of the present invention, the digital drive module, post-processing module and online detection module are all FPGA chips, so that a higher processing speed and data throughput can be achieved. The chaotic oscillation bandwidth of the superlattice device can reach the GHz level, and the physical random number output rate is less likely to be limited by the physical bandwidth of the superlattice work, which can ensure that the system output rate reaches more than 100Mbps.

[0036] In a specific implementation of the embodiment of the present invention, the number of sampling channels of the superlattice device and the analog-to-digital converter is equal; preferably, the number of sampling channels of the superlattice device and the analog-to-digital converter are both 4, see Figure 1 SL1-SL4, and ADC1-ADC4, the physical random number with sufficient entropy is 4 groups. In other embodiments of the present invention, the number of sampling channels of the superlattice device and the analog-to-digital converter can also be other numbers, which is determined according to actual conditions.

[0037] In a specific implementation of the embodiment of the present invention, the online detection module performs real-time detection on the randomness index of each group of physical random numbers, and once a certain path failure is found, an alarm signal is issued. At this time, the physical random numbers output by the online detection module can still be used, so there is no need to disable the random number sending system due to safety issues when a single path failure occurs. Each superlattice device works in parallel at the same time. Unless all superlattice devices work abnormally, the quality of the physical random numbers output by the system and the output rate of the physical random numbers will not be affected, so that the supply of random numbers to the application system can be guaranteed to be uninterrupted.

[0038] Example 2

[0039] An embodiment of the present invention provides a highly reliable physical random number generation method, comprising the following steps:

[0040] (1) using a digital driving module to generate a digital driving signal and sending it to a chaotic noise acquisition module, wherein the chaotic noise acquisition module includes a digital-to-analog converter, a plurality of superlattice devices, and a plurality of analog-to-digital converters;

[0041] (2) using the digital-to-analog converter to receive the digital driving signal and convert it into an analog waveform, and using the analog waveform to drive each superlattice device to generate chaotic oscillation; each analog-to-digital converter is respectively connected to the corresponding superlattice device, samples the chaotic oscillation generated by the corresponding superlattice device, and outputs an original random sequence;

[0042] (3) using a post-processing module to receive the original random sequences output by each analog-to-digital converter, and extracting randomness respectively to obtain multiple groups of physical random numbers with sufficient entropy;

[0043] (4) After bitwise XORing each group of physical random numbers using the online detection module, the numbers are sent to the output module for use by the application system, and are also sent to the digital drive module for generating digital drive signals. In the embodiment of the present invention, after bitwise XORing each group of physical random numbers and then outputting them, the entropy of the random numbers finally outputted will not be worse than that of the original groups of random numbers, so that the quality of the outputted random numbers is better.

[0044] In a specific implementation of the embodiment of the present invention, the digital drive module, post-processing module and online detection module are all FPGA chips, so that a higher processing speed and data throughput can be achieved. The chaotic oscillation bandwidth of the superlattice device can reach the GHz level, and the physical random number output rate is less likely to be limited by the physical bandwidth of the superlattice work, which can ensure that the system output rate reaches more than 100Mbps.

[0045] In a specific implementation of the embodiment of the present invention, the number of the superlattice devices is equal to that of the analog-to-digital converters; preferably, the number of the superlattice devices and the analog-to-digital converters are both 4, see Figure 1 SL1-SL4, and ADC1-ADC4, are four groups of physical random numbers with sufficient entropy.

[0046] In a specific implementation of the embodiment of the present invention, the online detection module performs real-time detection on the randomness index of each group of physical random numbers, and once a certain path failure is found, an alarm signal is issued. At this time, the physical random numbers output by the online detection module can still be used, so there is no need to disable the random number sending system due to safety issues when a single path failure occurs. Each superlattice device works in parallel at the same time. Unless all superlattice devices work abnormally, the quality of the physical random numbers output by the system and the output rate of the physical random numbers will not be affected, so that the supply of random numbers to the application system can be guaranteed to be uninterrupted.

[0047] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A highly reliable physical random number generation system, characterized in that: include: Digital drive module, chaotic noise acquisition module, post-processing module, online detection module, output module; The digital driving module generates a digital driving signal and sends it to the chaotic noise acquisition module; The chaotic noise acquisition module includes a digital-to-analog converter, a plurality of superlattice devices and a plurality of analog-to-digital converters; The digital-to-analog converter receives the digital driving signal and converts it into an analog waveform, and uses the analog waveform to drive each superlattice device to generate chaotic oscillation; Each analog-to-digital converter is connected to a corresponding superlattice device, samples the chaotic oscillation generated by the corresponding superlattice device, and outputs an original random sequence; The post-processing module receives the original random sequences output by each analog-to-digital converter, and performs randomness extraction respectively to obtain multiple groups of physical random numbers with sufficient entropy; The online detection module performs bitwise XOR on each group of physical random numbers and sends them to the output module for use by the application system. At the same time, it also sends them to the digital drive module for generating digital drive signals, forming a closed-loop system that continuously outputs random numbers. The online detection module performs real-time detection on the randomness index of each group of physical random numbers. Once a certain path failure is found, the physical random numbers output by the online detection module can still be used, and there is no need to disable the random number generation system due to safety issues when a single path failure occurs; The online detection module performs real-time detection on the randomness index of each group of physical random numbers, and sends out an alarm signal once a fault is found in a certain path.

2. A highly reliable physical random number generation system according to claim 1, characterized in that: The digital drive module, post-processing module and online detection module all use FPGA chips.

3. A highly reliable physical random number generation system according to claim 1, characterized in that: The number of the superlattice device is equal to the number of sampling channels of the analog-to-digital converter.

4. A highly reliable physical random number generation method, characterized in that: The following steps are involved: A digital driving module is used to generate a digital driving signal, and the digital driving signal is sent to a chaotic noise acquisition module, wherein the chaotic noise acquisition module includes a digital-to-analog converter, a plurality of superlattice devices, and a plurality of analog-to-digital converters; Using the digital-to-analog converter to receive the digital driving signal and convert it into an analog waveform, and using the analog waveform to drive each superlattice device to generate chaotic oscillation; Each analog-to-digital converter is connected to a corresponding superlattice device, samples the chaotic oscillation generated by the corresponding superlattice device, and outputs an original random sequence; The post-processing module is used to receive the original random sequences output by each analog-to-digital converter, and the randomness is extracted respectively to obtain multiple groups of physical random numbers with sufficient entropy; The online detection module performs bitwise XOR on each group of physical random numbers and sends them to the output module for use by the application system. At the same time, it is also sent to the digital drive module for generating digital drive signals, forming a closed-loop system that continuously outputs random numbers. The online detection module performs real-time detection on the randomness index of each group of physical random numbers. Once a certain path failure is found, the physical random numbers output by the online detection module can still be used, and there is no need to disable the random number generation system due to safety issues when a single path failure occurs; The online detection module is used to perform real-time detection on the randomness index of each group of physical random numbers. Once a fault is found in a certain path, an alarm signal is issued.

5. A highly reliable physical random number generation method according to claim 4, characterized in that: The digital drive module, post-processing module and online detection module all use FPGA chips.

6. A highly reliable physical random number generation method according to claim 4, characterized in that: The number of the superlattice device is equal to the number of sampling channels of the analog-to-digital converter.

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