Physical random number generator

Abstract

The invention relates to a physical random number generator including three modules, i.e., a random entropy source module, a data acquisition module and a data processing module. The physical random number generator realizes dual-way chaotic laser output firstly through utilizing the mutual coupling of lasers, and the output two-way chaotic laser is converted into an electric signal by a photoelectric detector after passing through a polarization controller, an adjustable attenuator, a beam splitter, an isolator and a light amplifier control element and then is converted into a binary bit stream by the data acquisition module. The binary bit stream is subjected to differentiate operation through a logic processor, and then, a random sequence is output. The physical random number generator can generate random numbers with high code rate and is simpler in structure.

Description

technical field [0001] The invention relates to a technique for generating a physical true random number, which can be applied to the field of IT and the like. Background technique [0002] Random numbers have important uses in information security, computer, material science, medicine, finance and many other fields. [0003] Generally, methods for generating random numbers can be divided into two categories: software-based methods and physical hardware-based methods. Random numbers generated by programming operations using algorithms are called pseudo-random numbers. This type of random number is easy to generate but easier to be attacked and cracked; another type of random number extracted from random phenomena in the real physical world is called true random number. [0004] The entropy source of the physical random number generator that produces true random numbers is selected from the natural randomness of the real world, so the random numbers it generates have the adv...

AI Technical Summary

Problems solved by technology

However, the efficiency of using these methods to generate high-quality true random numbers is low. The code rate of most physical random number generators is much lower than that of pseudo-random number generators, which is difficult to meet the real-time application requirements. Therefore, it is necessary to explore new sources of physical entropy.

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