Active Transistor RNG Circuit with MEMS Entropy
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Solution Overview
Problem
Current systems for generating high-quality randomness for cryptographic purposes often require low-power and compact solutions that can provide unpredictable and non-repeating outputs, which existing technologies struggle to achieve effectively.
Innovation Solution
A random number generator (RNG) circuit that incorporates micro-electromechanical systems (MEMS) structures and active transistor RNG circuitry, where the MEMS structures provide entropy through active oscillations, charge, resistance, capacitance, and inductance values, which are then used by the active transistor circuitry to generate a random number output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional random number generation methods are used, then the system can provide randomness output, but the quality of randomness is insufficient for high-security cryptographic applications
Solution Approach 1:
The patent combines MEMS structures with active transistor circuitry into a unified RNG system. The MEMS structures generate physical oscillations that are directly fed into the transistor circuitry, merging physical entropy generation with electronic random number generation in a single integrated device, thereby improving randomness quality without proportionally increasing complexity
Solution Approach 2:
The MEMS structures serve as an intermediary between environmental noise sources and the transistor circuitry. They convert ambient vibrations and physical disturbances into measurable oscillation patterns that the electronic circuit can process, acting as a bridge that enhances randomness quality while managing system complexity
2Reliability
If the RNG circuit uses more complex structures to improve randomness quality, then the randomness output quality improves, but the power consumption increases
Solution Approach 1:
The MEMS structures operate as dynamic, oscillating elements that harvest energy from environmental vibrations rather than requiring continuous high-power input. The active transistor circuitry is triggered by these oscillations, allowing the system to maintain high randomness quality while consuming power only during detection and processing phases, not during the entropy generation phase
Solution Approach 2:
The MEMS structures are designed to be self-activating through environmental noise and physical disturbances. They automatically generate oscillations from ambient conditions without requiring external power for the entropy generation process, thereby improving randomness quality while minimizing power consumption
3Volume of moving object
If the RNG circuit is designed to be compact, then the device size is reduced, but the ability to generate high-quality randomness is compromised
Solution Approach 1:
The MEMS structures are fabricated at the micro-scale and integrated directly within the transistor circuitry footprint. The entropy generation component (MEMS) is nested within or adjacent to the processing component (transistor circuit), allowing the entire RNG system to maintain compact dimensions while incorporating the physical oscillation mechanism necessary for high-quality randomness generation
4Reliability
If the system uses environmental noise as entropy source, then the randomness quality improves, but the system becomes sensitive to external bias and interference
Solution Approach 1:
The MEMS structures act as a controlled intermediary that filters and shapes environmental noise into specific oscillation patterns. They selectively transduce certain frequency ranges and physical disturbance types while attenuating others, thereby maintaining sensitivity to useful entropy sources while reducing vulnerability to harmful external bias and interference
Solution Approach 2:
The system is designed to be sensitive to specific local characteristics of environmental noise (certain frequency ranges, vibration modes) rather than all external stimuli equally. The MEMS structures are tuned to respond to particular oscillation patterns, creating localized sensitivity that captures entropy while rejecting unwanted external bias
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 proposed RNG circuit effectively generates high-quality random numbers by harnessing environmental noise and ensuring that the output is non-deterministic, even in the presence of external bias, thus enhancing the security of cryptographic operations.
Implementation Method 1
one or more micro-electromechanical (MEMS) structures configured to provide an output, wherein the output includes active oscillations, charge, resistance, capacitance, and/or inductance values
Implementation Method 2
active transistor RNG circuitry communicatively coupled to the one or more MEMS structures. The active transistor RNG circuitry is configured to generate a random number output based on the output provided by the one or more MEMS structures
Data Source
AI summary
Systems and methods for an active transistor RNG circuit with MEMS entropy are described herein. In one example, an RNG circuit includes one or more MEMS structures configured to provide an output, wherein the output includes active oscillations, charge, resistance, capacitance, and/or inductance values. The RNG circuit further includes active transistor RNG circuitry communicatively coupled to the one or more MEMS structures. The active transistor RNG circuitry is configured to generate a random number output based on the output by the one or more MEMS structures. The random number output generated by the active transistor RNG circuitry is an output of the RNG circuit.