True random number generator based on liquid molecule Brownian movement

Abstract

The invention discloses a true random number generator which comprises a random number acquiring unit and a random number generating unit. The random number acquiring unit comprises a high-pressure-resistant closed transparent liquid pool containing the mixture formed by particles performing Brownian movement, a high-speed microimaging device periodically shooting the internal cross section of the mixture so as to obtain multiple frames of pictures. The random number generating unit comprises a digitization processor for processing the multiple frames of pictures so as to obtain a preliminary random number string A0 and a postprocessor for processing A0 so as to obtain a random number sequence.

Description

technical field [0001] This application relates to random number generators, and more particularly to a true random number generator based on the Brownian motion of liquid molecules. Background technique [0002] Random numbers play an important role in fields such as cryptography, simulation, and integrated circuit testing. A random number sequence is usually a combination of random binary sequences. According to whether it is reproducible and predictable, random numbers can be divided into pseudo-random numbers and true random numbers. Pseudo-random numbers are not really random, they are usually calculated by various electronic devices such as computers, so once you know the generation method and some parameters (such as random number seeds), you can get exactly the same pseudo-random Therefore, for the security of communication, a generator capable of generating true random numbers is required. [0003] True random numbers can usually only be obtained through physical ...

AI Technical Summary

Problems solved by technology

Current true random number generators usually generate true random numbers based on circuit noise, etc., but the noise is usually small, and it is difficult to directly and accurately measure and quantify it. The usual practice is to measure it after amplification

However, since the amplifier is not absolutely linearly amplified, the randomness of the current signal obtained after amplifying the small noise is bound to be affected

Other true random number generation methods, such as using metastable flip-flops to generate true random numbers, usually have problems such as insufficient randomness

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