Experimental Analyses of a Noise-Based True Random Number Generator
- 8 March 2023
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 0915-0918
- https://doi.org/10.1109/ccwc57344.2023.10099239
Abstract
This work presents a fast, low power and simple structure noise-based true random number generator (TRNG) using discrete components and devices such as resistor., capacitor, diode., transistor., operational amplifier etc. Two NPN 2N3904 BJT transistors are employed in the noise-source circuit whereby the collector terminal of one transistor is unconnected. A high electric field is induced by reverse biasing the emitter-base junction under high voltage. Current is injected into the base which lowers the noise voltage at the output node and then removes the transistor from breakdown region. Another random pulse also puts the transistor back into breakdown and the cycle continues. Subsequently, the noise signal generated is amplified by two LM741 op-amp each with a gain of 100. We employed 4007 series as digitizer to convert the amplified noise to digital pulses. The post processing technique is implemented with XOR operation., and the result shows the output data generated by TRNG pass all NIST SP800-22 tests.Keywords
Funding Information
- Louisiana State University (002128)
- Louisiana Board of Regents (LEQSF (2018-21)-RD-A-09)
- Office of Research & Economic Development (004475)
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