Multisource input true random number generator circuit structure

Abstract

The invention discloses a multisource input true random number generator circuit structure. Multiple noise generating circuits of different types are used as noise sources; with input selection of an option switch, the noise is input into a sampling correcting circuit; on one hand, the input result enters into an output processing module, and on the other hand, the input result enters into a random number counter; the random number counter counts the generated random number, and feeds back the output result to the option switch; then the signals are randomly selected from the multiple noise generating circuits and then output. In the process, due to the randomness of selection from the multiple noise sources, the randomness of the sampling correcting output, and the randomness of application of the random number counter, the pseudo-randomness generated by the original single noise generating circuit due to long-time working can be eliminated wholly. Proved by the theory and experiments, the true random number generator utilizes multiple noise sources and the random number counter to realize feedback, so that the randomness of the long-range data is better than the original random number generator realized by the single noise source.

Description

technical field [0001] The invention relates to a true random number generator using multi-noise source input, and belongs to the technical field of key management in information security systems. Background technique [0002] The random number generator is an analog-digital mixed security chip, which enhances the influence of random noise in the circuit, and samples high-speed random "0" and "1" sequences, which can pass the randomness test. [0003] The random number generator plays a very important role in the security information system. As the core component of the security information system, any cryptographic machine, cryptographic device or cryptographic protocol cannot do without the random number generator. In a well-designed cryptographic component, there must be two sources of disturbance, one mathematical and one physical. Both are indispensable. Mathematical chaos sources can be realized by mathematical algorithms, while physical chaos sources must be realize...

AI Technical Summary

Problems solved by technology

However, in practical applications, it is found that due to sampling a single noise source, pseudo-randomness will still appear after a long time, and there is still a risk of cracking for encryption devices that need to work for a long time

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