True random number generator and method for mcu to convert bridge voltage at random intervals

Abstract

The invention discloses a true random number generator and a generating method for converting bridge voltage at random intervals by an MCU, including an MCU, a bridge module and an amplifier. The MCU includes an application module, a random number generation module and an ADC module; the power supply VCC passes through The switch SW is respectively connected to the bridge module and the amplifier, the output terminal of the bridge module is connected to the amplifier, the output terminal of the amplifier is connected to the ADC module, the ADC module is connected to the random number generator, and the random number generator is connected to the application module. In the present invention, the output of the electric bridge is passed through the amplifier, and then the output is converted by the ADC. The size of the number of true random numbers can be controlled by the application module, and its working mode is quite flexible, which can meet various application scenarios of the communication system and various requirements. An encryption algorithm with a random number bit width.

Description

technical field [0001] The invention relates to a true random number generator and a generating method for converting bridge voltages at random intervals by an MCU. Background technique [0002] In recent years, with the continuous development of communication technology, especially now that we are about to enter the 5G era, the communication rate is getting higher and higher, and the communication quality is getting better and better. These issues that were generally concerned by people before have become less and less popular. Take it seriously. Now, people have shifted the focus of their attention, they no longer focus on the communication speed or communication quality of the communication system, they are now focusing on whether the communication information is safe or not. Especially in today's information age, the security of information directly affects the interests of the country, enterprises and individuals, because the 21st century is the age of information. In ...

AI Technical Summary

Problems solved by technology

[0006] The disadvantages of the prior art are: a separate true random number generator chip needs to purchase a dedicated chip at first, which is expensive and subject to human constraints.

FPGA all-digital true random numbers are more expensive, and in application scenarios that do not require FPGAs and must be implemented by microcontrollers, DSPs, and ARMs, a true random number generation solution suitable for these MCUs is required; microcontrollers are implemented by programming There are many solutions for pseudo-random number generators, but they are easy to be cracked and are not suitable for occasions with relatively high security information requirements.

At present, there is also a circuit structure that uses a single-chip ADC to convert the voltage of a pure resistance voltage divider circuit to realize a true random number. However, the output voltage of this pure resistance structure has a small range of variation. If the circuit noise is small, the voltage value obtained after the voltage division will change. It is not large, and if the accuracy of the ADC is not high enough, the collected voltage value may change little or not, so the randomness of the obtained random number is not high

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