Hybrid Random Number Generator Entropy Control Circuit
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Solution Overview
Problem
Existing random number generators, particularly pseudo random number generators (PRNGs), are vulnerable to prediction if the initial seed value is known, and true random number generators (TRNGs) produce numbers at a slower rate, necessitating frequent reseeding to maintain security.
Innovation Solution
A circuit comprising free-running oscillators with adjustable frequencies and a von Neumann de-correlator to produce and adjust the entropy of a random sequence, ensuring unpredictable and high-quality random number generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a pseudo random number generator (PRNG) is used, then random numbers can be produced at a fast rate, but the sequence becomes predictable if the seed value is known
Solution Approach 1:
The patent combines a PRNG circuit with a TRNG circuit into a hybrid system. The TRNG provides unpredictable seed values periodically to reseed the PRNG, maintaining both high generation speed and cryptographic security. The PRNG handles bulk random number generation while the TRNG ensures unpredictability through physical entropy sources.
Solution Approach 2:
An entropy pool acts as an intermediary between the TRNG and PRNG. The TRNG fills the entropy pool with random values, which then seeds the PRNG. This mediator ensures that the PRNG receives sufficient entropy without direct coupling, maintaining security while enabling fast generation.
2Reliability
If a true random number generator (TRNG) is used, then unpredictability is maximized, but the generation rate is slower requiring frequent reseeding
Solution Approach 1:
The TRNG circuit continuously or periodically fills an entropy pool with random values in advance. This preliminary action ensures that when the PRNG needs reseeding, sufficient entropy is already available, avoiding frequent TRNG activations and maintaining high overall generation rates.
Solution Approach 2:
The system dynamically switches between TRNG and PRNG operation modes. The TRNG operates at low duty cycle to maintain entropy supply, while the PRNG handles the majority of random number generation requests. This dynamic allocation optimizes both security and performance.
3Productivity
If oscillators are used to generate random numbers through sampling, then fast generation is achieved, but power consumption and noise interference increase
Solution Approach 1:
The oscillators are activated periodically rather than continuously. The TRNG uses oscillators to generate entropy samples at specific intervals, then enters a low-power state. The PRNG continues generating random numbers using stored entropy without requiring continuous oscillator operation, significantly reducing average power consumption.
Solution Approach 2:
The system uses ambient thermal noise and other environmental electromagnetic interference as entropy sources whenever possible, eliminating the need for active oscillator operation during entropy collection. This self-service approach to entropy gathering minimizes power consumption while maintaining random number generation capability.
Data Source
AI summary
A random number generator includes a first circuit producing a random sequence of values, the first circuit having an adjustable input that changes the entropy of the random sequence of numbers; a second circuit receiving the random sequence of values from the first circuit and producing an output indicative of the degree of entropy of the random sequence of values, and a third circuit that adjusts the adjustable input of the first circuit in response to the output of the second circuit.