Method and system for generating truly random numbers based on parity of physical noises

Abstract

The invention relates to a method and a system for generating truly random numbers based on the parity of physical noises. The method is used for generating truly random numbers according to the parity of physical noises subjected to analog-to-digital conversion, and comprises the following steps: 1) generating analog noise signals through physical noise sources; 2) carrying out analog / digital conversion on the acquired analog noise signals generated by the physical noise sources so as to form digital noise signals; 3) generating binary random numbers according to the parity of digital noise signals subjected to conversion; and 4) repeating the step 2) and the step 3), thus obtaining a sequence containing a plurality of random numbers. The method disclosed by the invention can be implemented by using various noise sources, and the quality of generated random numbers is not affected by the environment; the method is good in stability and strong in anti-interference ability; and the method can immediately generate random numbers, and the random number generating efficiency is high. The system disclosed by the invention is simple in components, integrated easily, and low in manufacturing cost.

Description

technical field [0001] The invention relates to the technical field of random number generators, in particular to a method and system for generating true random numbers based on the parity of physical noise, which can generate true random number sequences with high efficiency, high stability and in real time. Background technique [0002] High-quality random numbers have very important applications in the fields of confidential communication, information security, identity verification, cryptographic protocols, and digital signatures. In addition, commercial lotteries and gaming machines also require high-quality random numbers to achieve their unpredictability. At present, how to generate high-quality random numbers at high speed is an important research direction of cryptography and even information security. [0003] An ideal random number generator generates data sequences that are uniformly distributed and independent of each other. According to the method of generati...

AI Technical Summary

Problems solved by technology

At present, computers and Internet security systems all use pseudo-random number generators. This kind of random sequence generated by algorithms will repeat after a certain length, which is very dangerous for cryptographic systems that require high security.

The generation of true random numbers relies on the random characteristics of natural physical phenomena. These physical random sources are unpredictable, such as lava lamps, radioactive decay, atmospheric noise, thermal noise of circuits, etc. Therefore, true random numbers can be completely eliminated. To solve the periodic problem of pseudo-random numbers, the generated random number sequence has the characteristics of uncertainty, unpredictability and non-repeatability. Obviously, for information systems, the pseudo-random numbers generated by mathematical methods are not as good as those generated by physical methods. The security of true random numbers is high

[0004] At present, there are some true random number generators on the market based on random physical phenomena. The main method for generating true random numbers is the identification amplitude method, which is to specify an identification amplitude, and then sample the physical noise source. If the sampling obtained If the signal is higher than the specified identification amplitude, it will output 1, otherwise it will output 0, thus generating a sequence of binary random numbers. However, this method has poor stability, poor anti-interference ability, and is easily affected by environmental factors such as temperature and pressure. Random performance for generating random number sequences

In addition, there is another method to generate true random numbers is the time interval method. This method generates random number sequences according to the number of digits in the sequence fragments. Although this method has improved stability, the efficiency is relatively low and requires A very long sequence generates several random numbers, and this method cannot output the random number sequence immediately, because the generation principle determines that there is a delay in outputting the random number sequence

[0005] Therefore, it is difficult to generate a true random number with both high efficiency and stability. At present, there is no method in the true random number generation method that can not only ensure the high-efficiency and real-time generation of random number sequences, but also ensure the generation of random number sequences. The stability makes it have good anti-interference ability

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