Actively Stabilized Random Number Generator Using Feedback Control
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Solution Overview
Problem
Current true-random number generators are either costly and slow due to reliance on quantum uncertainty or exhibit vulnerabilities from non-ideal realization of complex chaotic classical dynamics, and are sensitive to environmental changes, making them unsuitable for large-scale integration and secure applications like encryption.
Innovation Solution
An actively stabilized random number generator (ASRNG) utilizing a chaotic physical circuit with a unimodal map and feedback controller, which generates true random numbers through an iterated function with a positive entropy rate and an operating parameter between 1 and 2, mitigating vulnerabilities and environmental sensitivity via kneading theory and feedback control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If quantum uncertainty-based devices are used for true-random generation, then security is improved, but cost and speed deteriorate
Solution Approach 1:
The patent replaces quantum mechanical systems with a classical electronic chaotic system based on the logistic map. The chaotic physical circuit uses voltage dynamics to generate true random numbers, substituting quantum uncertainty with deterministic chaos that is computationally intractable to predict, thereby achieving security without quantum hardware costs and speed limitations
Solution Approach 2:
The patent changes the operating parameter β of the logistic map to specific values (β=1.99999 or β=2.0) that maximize entropy production. By tuning this parameter, the system achieves optimal randomness generation rate while maintaining security, resolving the contradiction between speed and security through parameter optimization
2Productivity
If complex chaotic classical dynamics are used for true-random generation, then speed is improved, but vulnerabilities increase due to non-ideal realization
Solution Approach 1:
The patent implements a feedback controller that continuously monitors the chaotic system's output and adjusts the operating parameter β to maintain optimal entropy production. This feedback mechanism compensates for environmental disturbances and component variations, ensuring the system remains in the chaotic regime and preventing vulnerabilities from non-ideal realization
Solution Approach 2:
The system uses its own output to regulate itself through the feedback controller, which automatically adjusts parameters to maintain optimal chaotic behavior. This self-regulation ensures the system compensates for its own non-idealities and environmental variations without external intervention, reducing vulnerabilities
3Reliability
If physical property-based generators are used, then true-random generation is achieved, but environmental sensitivity increases
Solution Approach 1:
The feedback controller monitors environmental parameter changes and dynamically adjusts the operating parameter β to compensate for these changes. This active stabilization maintains the system in the optimal chaotic regime despite temperature or other environmental variations, achieving true-random generation without environmental sensitivity
Data Source
AI summary
An actively stabilized random number generator includes a random number generator and a feedback controller. The random number generator includes a chaotic physical circuit realizing an iterated function. The iterated function is configured to produce a trajectory of iterates and has an operating parameter β and a desired Markov operating point. A binary bit converter has a symbol function configured to produce binary symbols from the trajectory of iterates and a maximal kneading sequence. The feedback controller is configured to observe the maximal kneading sequence within the trajectory of iterates and adjust the operating parameter to the desired Markov operating point.