GM/T 0078-2020 PDF English
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GM/T 0078-2020: The design guidelines for cryptographic random number generation module---This is an excerpt. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.), auto-downloaded/delivered in 9 seconds, can be purchased online: https://www.ChineseStandard.net/PDF.aspx/GMT0078-2020
GM
CRYPTOGRAPHY INDUSTRY STANDARD
ICS 35.040
CCS L 80
The Design Guidelines for Cryptographic Random
Number Generation Module
Issued on. DECEMBER 28, 2020
Implemented on. JULY 1, 2021
Issued by. State Cryptography Administration
Table of Contents
Foreword... 3
1 Scope... 4
2 Normative References... 4
3 Terms and Definitions... 4
4 Abbreviations... 5
5 General Model of Random Number Generation Module... 5
6 Design Principle of Physical Random Source Circuit... 6
6.1 Principle of Chaotic Dynamical System... 6
6.2 Principle of Phase Jitter... 8
6.3 Principle of Direct Thermal Noise Amplification... 9
6.4 Synthesis of Multi-channel Physical Random Sources... 11
7 Failure Detection of Physical Random Sources... 12
8 Randomness Detection of Physical Random Sources... 12
9 Design Method of Post-processing Algorithm... 12
9.1 Design Requirements for Post-processing Algorithm... 12
9.2 Cryptographic Function Method... 12
9.3 Lightweight Post-processing Methods... 14
Appendix A (informative) Circuit Examples of Physical Random Sources... 16
Foreword
This Standard was drafted in accordance with the rules in GB/T 1.1-2020 Directives
for Standardization - Part 1.Rules for the Structure and Drafting of Standardizing
Documents.
Please be noted that certain content of this document might involve patents. The
institution issuing this document does not undertake the responsibility of identifying
these patents.
This Standard was proposed by and shall be under the jurisdiction of Cryptography
Standardization Technical Committee.
The drafting organizations of this Standard. Beijing HSEC Technology Co., Ltd.;
Commercial Cryptography Testing Center of State Cryptography Administration;
Institute of Software Chinese Academy of Sciences; Institute of Information
Engineering, CAS; Nations Technologies Inc.; CEC Huada Electronic Design Co., Ltd.;
Beijing Smartchip Microelectronics Technology Co., Ltd.
The main drafters of this Standard. Zhang Wenjing, Luo Peng, Yu Qunhui, Fan Limin,
Ma Yuan, Yang Xianwei, Li Dan, Gan Jie, Xia Luning.
The Design Guidelines for Cryptographic Random
Number Generation Module
1 Scope
This Standard specifies the design requirements for cryptographic hardware random
number generation module.
This Standard is applicable to the guidance on the research, development and test of
random number generation module.
2 Normative References
The content of the following documents constitutes indispensable clauses of this
document through normative references in the text. In terms of references with a
specified date, only versions with a specified date are applicable to this document. In
terms of references without a specified date, the latest version (including all the
modifications) is applicable to this document.
GM/T 0005 Randomness Test Specification
GM/T 0008 Cryptography Test Criteria for Security IC
3 Terms and Definitions
What is defined in GM/T 0005 and GM/T 0008, and the following terms and definitions
are applicable to this document.
3.1 Random Number Generation Module
Random number generation module refers to a circuit that utilizes the natural
randomness of the real world to extract random quantities from random physical
processes and undergoes transformation processing to output random numbers.
3.2 Thermal Noise
Thermal noise, which is also known as white noise, is caused by thermal vibration of
electrons in the conductor. It exists in all electronic devices and transmission media. It
is the result of temperature changes but is not affect by frequency changes. Thermal
noise is distributed in the same form in all frequency spectra, and it cannot be
eliminated.
4 Abbreviations
The following abbreviations are applicable to this document.
CBC. Cipher Block Chaining
5 General Model of Random Number Generation Module
The general model of random number generation module is shown in Figure 1.
The random number generation module has two outputs, one is the random number
sequence output, and the other is the random source detection output that provides
detection. The randomness of the output random number sequence shall comply with
the stipulations of GM/T 0005.Random source detection output is mainly used to
detect the basic randomness of physical random sources.
6 Design Principle of Physical Random Source Circuit
6.1 Principle of Chaotic Dynamical System
6.1.1 Typical model of principle
Utilizing the characteristics of chaotic function to design a chaotic system is to take
random noise as minor disturbance of the chaotic system. Since the output of the
system is affected by the random noise in the system, the output sequence of the
system is unpredictable, and random sequence may be generated. The realization of
the physical random sources based on the principle of the chaotic dynamical system
mainly considers the circuit realization of the chaotic function and the realization of
random noise.
6.1.2 Circuit design requirements
6.1.4 Example of circuit
A circuit example of physical random sources based on the principle of discrete chaotic
Sampling
6.2.1 Typical model of principle
The method of utilizing phase jitter to generate random numbers has been extensively
applied and can be conveniently designed and implemented in both digital and analog
circuits.
6.2.2 Circuit design requirements
6.2.2.1 Random bit generation rate
In circuit design, the sampling clock is a slow clock signal. The sampling frequency of
the sampling clock determines the rate of random bit sequence generation.
6.3 Principle of Direct Thermal Noise Amplification
6.3.1 Typical model of principle
The principle of direct thermal noise amplification is to adopt an amplifying circuit to
directly amplify the thermal noise in the circuit, and then, output a random source
sequence through comparison.
6.3.2 Circuit design requirements
6.3.2.1 Thermal noise amplitude
Resistor thermal noise is one of the important modes to design noise source. In terms
of the resistor thermal noise source, its thermal noise is only related to temperature
and resistance value; it has nothing to do with the passed current. Its unilateral spectral
density S(f) is shown in Formula (2); the noise power Vn2 is shown in Formula (3).
7 Failure Detection of Physical Random Sources
The failure detection of physical random sources is to detect the final output sequence
of the circuit part of the physical random sources when the random number generation
module is working.
8 Randomness Detection of Physical Random Sources
The randomness detection of physical random sources is to detect the output signal of
the physical random sources before post-processing when the random number
generation module is working.
9 Design Method of Post-processing Algorithm
9.1 Design Requirements for Post-processing Algorithm
The basic principle of the post-processing algorithm is that the average entropy per bit
cannot be reduced. In other words, the post-processing module inputs n bits and
outputs m bits, and it must be guaranteed that n ≥ m, in which, the premise of n = m is
that the output sequence of the physical random sources passes the detection by GM/T
0005.
9.2 Cryptographic Function Method
9.2.2 Post-processing algorithm based on hash functions
The post-processing algorithm based on hash functions needs to adopt approved
secure hash functions.
9.2.3 Post-processing algorithm based on m-sequence
The post-processing is realized by m-sequence with a length of K through linear
feedback shift register or non-linear feedback shift register. The input of the physical
random sources is synchronized with the cyclic shift of the shift register, and the
feedback bit and the current bit of the digitized noise signal are XORed and output.
The m-sequence method shall satisfy the following requirements.
9.3.2 XOR chain method
The XOR chain method obtains the internal output sequence by combining the output
sequences of physical random sources through a multi-level trigger. Set the input
sequence as Xi, and each time the result of the adjacent n-bit XOR value is used as
the output. In other words, is used
9.3.3 Odd-even grouping method
Set every n bits of the input sequence Xi as a group, in which, the number of 1 in the
n bits data is odd / even and expressed as 1; the number of 1 is even / odd and
expressed as 0.The specific data of n is determined by the probability deviation e of
0, 1 output from the original random number generation module and the allowable 0,
1 probability deviation e after correction,.
9.3.4 m-LSB method
Set every n bits of the input sequence Xi as a group, for n-tuple (Xn i+1 Xn i+2...Xn
i+n), discard high (n - m) bits, output low m-bits as the processed data output.
GM/T 0078-2020
GM
CRYPTOGRAPHY INDUSTRY STANDARD
ICS 35.040
CCS L 80
The Design Guidelines for Cryptographic Random
Number Generation Module
Issued on. DECEMBER 28, 2020
Implemented on. JULY 1, 2021
Issued by. State Cryptography Administration
Table of Contents
Foreword... 3
1 Scope... 4
2 Normative References... 4
3 Terms and Definitions... 4
4 Abbreviations... 5
5 General Model of Random Number Generation Module... 5
6 Design Principle of Physical Random Source Circuit... 6
6.1 Principle of Chaotic Dynamical System... 6
6.2 Principle of Phase Jitter... 8
6.3 Principle of Direct Thermal Noise Amplification... 9
6.4 Synthesis of Multi-channel Physical Random Sources... 11
7 Failure Detection of Physical Random Sources... 12
8 Randomness Detection of Physical Random Sources... 12
9 Design Method of Post-processing Algorithm... 12
9.1 Design Requirements for Post-processing Algorithm... 12
9.2 Cryptographic Function Method... 12
9.3 Lightweight Post-processing Methods... 14
Appendix A (informative) Circuit Examples of Physical Random Sources... 16
Foreword
This Standard was drafted in accordance with the rules in GB/T 1.1-2020 Directives
for Standardization - Part 1.Rules for the Structure and Drafting of Standardizing
Documents.
Please be noted that certain content of this document might involve patents. The
institution issuing this document does not undertake the responsibility of identifying
these patents.
This Standard was proposed by and shall be under the jurisdiction of Cryptography
Standardization Technical Committee.
The drafting organizations of this Standard. Beijing HSEC Technology Co., Ltd.;
Commercial Cryptography Testing Center of State Cryptography Administration;
Institute of Software Chinese Academy of Sciences; Institute of Information
Engineering, CAS; Nations Technologies Inc.; CEC Huada Electronic Design Co., Ltd.;
Beijing Smartchip Microelectronics Technology Co., Ltd.
The main drafters of this Standard. Zhang Wenjing, Luo Peng, Yu Qunhui, Fan Limin,
Ma Yuan, Yang Xianwei, Li Dan, Gan Jie, Xia Luning.
The Design Guidelines for Cryptographic Random
Number Generation Module
1 Scope
This Standard specifies the design requirements for cryptographic hardware random
number generation module.
This Standard is applicable to the guidance on the research, development and test of
random number generation module.
2 Normative References
The content of the following documents constitutes indispensable clauses of this
document through normative references in the text. In terms of references with a
specified date, only versions with a specified date are applicable to this document. In
terms of references without a specified date, the latest version (including all the
modifications) is applicable to this document.
GM/T 0005 Randomness Test Specification
GM/T 0008 Cryptography Test Criteria for Security IC
3 Terms and Definitions
What is defined in GM/T 0005 and GM/T 0008, and the following terms and definitions
are applicable to this document.
3.1 Random Number Generation Module
Random number generation module refers to a circuit that utilizes the natural
randomness of the real world to extract random quantities from random physical
processes and undergoes transformation processing to output random numbers.
3.2 Thermal Noise
Thermal noise, which is also known as white noise, is caused by thermal vibration of
electrons in the conductor. It exists in all electronic devices and transmission media. It
is the result of temperature changes but is not affect by frequency changes. Thermal
noise is distributed in the same form in all frequency spectra, and it cannot be
eliminated.
4 Abbreviations
The following abbreviations are applicable to this document.
CBC. Cipher Block Chaining
5 General Model of Random Number Generation Module
The general model of random number generation module is shown in Figure 1.
The random number generation module has two outputs, one is the random number
sequence output, and the other is the random source detection output that provides
detection. The randomness of the output random number sequence shall comply with
the stipulations of GM/T 0005.Random source detection output is mainly used to
detect the basic randomness of physical random sources.
6 Design Principle of Physical Random Source Circuit
6.1 Principle of Chaotic Dynamical System
6.1.1 Typical model of principle
Utilizing the characteristics of chaotic function to design a chaotic system is to take
random noise as minor disturbance of the chaotic system. Since the output of the
system is affected by the random noise in the system, the output sequence of the
system is unpredictable, and random sequence may be generated. The realization of
the physical random sources based on the principle of the chaotic dynamical system
mainly considers the circuit realization of the chaotic function and the realization of
random noise.
6.1.2 Circuit design requirements
6.1.4 Example of circuit
A circuit example of physical random sources based on the principle of discrete chaotic
Sampling
6.2.1 Typical model of principle
The method of utilizing phase jitter to generate random numbers has been extensively
applied and can be conveniently designed and implemented in both digital and analog
circuits.
6.2.2 Circuit design requirements
6.2.2.1 Random bit generation rate
In circuit design, the sampling clock is a slow clock signal. The sampling frequency of
the sampling clock determines the rate of random bit sequence generation.
6.3 Principle of Direct Thermal Noise Amplification
6.3.1 Typical model of principle
The principle of direct thermal noise amplification is to adopt an amplifying circuit to
directly amplify the thermal noise in the circuit, and then, output a random source
sequence through comparison.
6.3.2 Circuit design requirements
6.3.2.1 Thermal noise amplitude
Resistor thermal noise is one of the important modes to design noise source. In terms
of the resistor thermal noise source, its thermal noise is only related to temperature
and resistance value; it has nothing to do with the passed current. Its unilateral spectral
density S(f) is shown in Formula (2); the noise power Vn2 is shown in Formula (3).
7 Failure Detection of Physical Random Sources
The failure detection of physical random sources is to detect the final output sequence
of the circuit part of the physical random sources when the random number generation
module is working.
8 Randomness Detection of Physical Random Sources
The randomness detection of physical random sources is to detect the output signal of
the physical random sources before post-processing when the random number
generation module is working.
9 Design Method of Post-processing Algorithm
9.1 Design Requirements for Post-processing Algorithm
The basic principle of the post-processing algorithm is that the average entropy per bit
cannot be reduced. In other words, the post-processing module inputs n bits and
outputs m bits, and it must be guaranteed that n ≥ m, in which, the premise of n = m is
that the output sequence of the physical random sources passes the detection by GM/T
0005.
9.2 Cryptographic Function Method
9.2.2 Post-processing algorithm based on hash functions
The post-processing algorithm based on hash functions needs to adopt approved
secure hash functions.
9.2.3 Post-processing algorithm based on m-sequence
The post-processing is realized by m-sequence with a length of K through linear
feedback shift register or non-linear feedback shift register. The input of the physical
random sources is synchronized with the cyclic shift of the shift register, and the
feedback bit and the current bit of the digitized noise signal are XORed and output.
The m-sequence method shall satisfy the following requirements.
9.3.2 XOR chain method
The XOR chain method obtains the internal output sequence by combining the output
sequences of physical random sources through a multi-level trigger. Set the input
sequence as Xi, and each time the result of the adjacent n-bit XOR value is used as
the output. In other words, is used
9.3.3 Odd-even grouping method
Set every n bits of the input sequence Xi as a group, in which, the number of 1 in the
n bits data is odd / even and expressed as 1; the number of 1 is even / odd and
expressed as 0.The specific data of n is determined by the probability deviation e of
0, 1 output from the original random number generation module and the allowable 0,
1 probability deviation e after correction,.
9.3.4 m-LSB method
Set every n bits of the input sequence Xi as a group, for n-tuple (Xn i+1 Xn i+2...Xn
i+n), discard high (n - m) bits, output low m-bits as the processed data output.
......
Source: Above contents are excerpted from the full-copy PDF -- translated/reviewed by: www.ChineseStandard.net / Wayne Zheng et al.
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