True Random Number Generator Using Differential Oscillator Phase Inversion
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Solution Overview
Problem
True random number generators face issues with generating unbiased random numbers due to noise processing methods and are vulnerable to external attacks, which can damage their security functionality.
Innovation Solution
A true random number generator utilizing a differential structure oscillator with cascaded unit cells, including PMOS and NMOS transistors, and a phase detector to count oscillations until phase inversion occurs, generating a seed for random number generation, and a post-processing unit to enhance entropy and resilience against external conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If noise signal is amplified or accumulated to generate random numbers, then random number generation capability is improved, but bias in random numbers and vulnerability to external attacks worsen
Solution Approach 1:
The patent converts the harmful effect of external attacks and noise biases into a beneficial feature by using the oscillator's natural instability and noise as the core entropy source. The system deliberately exploits these previously harmful elements to generate high-entropy random numbers, making the system more resistant to attacks while improving random number quality.
Solution Approach 2:
The patent replaces traditional software-based pseudo-random number generation with a physical hardware oscillator system. This substitution of mechanical/physical processes for computational methods provides true entropy from physical noise, eliminating vulnerabilities to computational attacks while maintaining high generation capability.
2Productivity
If traditional noise processing methods are used, then random number generation is achieved, but bias in generated random numbers occurs
Solution Approach 1:
The patent changes the operating parameters of the oscillator system by using specific transistor configurations (PMOS and NMOS in differential pair), optimizing bias currents, and tuning oscillation frequencies to maximize noise entropy while minimizing bias. This parameter optimization ensures uniform random number distribution.
Solution Approach 2:
The patent uses a composite structure combining PMOS and NMOS transistors in a differential oscillator configuration. This composite device structure leverages the complementary characteristics of both transistor types to enhance noise generation while canceling out systematic biases, producing higher quality random numbers.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution provides a stable, high-entropy random number generator that is resistant to external attacks and changes, ensuring secure and unbiased random number generation.
Implementation Method 1
an oscillator configured to output signals and oscillate a random number of times due to noise until phases of the signals being output are inverted with respect to each other after initialization
Implementation Method 2
a P-type metal oxide semiconductor (PMOS) transistor and an N-type metal oxide semiconductor (NMOS) transistor connected between a driving voltage and a common node and having gate electrodes connected to each other to receive an input signal
Implementation Method 3
input signal degrading resistances connected between a drain electrode of the PMOS transistor and a drain electrode of the NMOS transistor and configured to reduce influence of the input signal on an output signal and increase influence of noise
Data Source
AI summary
Provided are a true random number generator and an oscillator. The random number generator includes an oscillator configured to output signals and oscillate a random number of times until phases of the signals being output are inverted with respect to each other after initialization, and a counter configured to count the number of oscillations. The counted number of oscillations is used as a seed for generating a random number.