True random number generator and realization method thereof

Abstract

The invention provides a true random number generator and a realization method of the rue random number generator. The realization method comprises the steps: after a VDD / VSS is electrified, a power management unit starts working and provides voltage for all units of the true random number generator; a biasing circuit provides a biasing voltage signal for a second clock source; the biasing circuit in the second clock source provides a biasing voltage for a voltage-controlled oscillator; after being processed by a processing unit, a signal generated from a noise source is used as a voltage signal of an input signal of the voltage-controlled oscillator, and an output signal of the voltage-controlled oscillator is used as the output CLK2 of the second clock source; a signal generated from a circular oscillator is processed by a buffer to obtain a signal which is used as the output CLK1 of a first clock source; digital mixing on the received CLK1 and CLK2 is conducted by a sampler (3) to generate random data; and a post-processing unit processes the received random data of the sampler and outputs a random sequence. With the adoption of true random number generator and the realization method, the phase noise of the oscillation signals can be improved, and the random characteristic of the generated random data is greatly enhanced.

Description

technical field [0001] The invention belongs to the field of information security, and in particular relates to a true random number generator and its realization method. Background technique [0002] In modern information security technology, cryptographic technology is widely used, and the key used for encryption and decryption of both communication parties is particularly critical, and the key is generally generated by a random number generator (Random Number Generator, RNG). Therefore, the performance of the random number generator directly determines the security of the key, that is, determines the security of the cryptosystem. [0003] Random number generators can be divided into pseudo random number generators (PRNG) and true random number generators (TRNG). Pseudo-random numbers are generated by seeds and a certain mathematical algorithm. The sequence period length is limited, the randomness is poor, and it is predictable. It is generally used in occasions with low ...

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Problems solved by technology

[0005] In the implementation scheme of the true random number generator, the direct amplification method mainly uses the physical noise in the circuit, but the circuit implementation is easily affected by non-ideal factors such as switching noise, substrate coupling, crosstalk, etc., which greatly reduces the randomness; the discrete time The chaos method uses the unpredictability of the chaotic circuit and its sensitive dependence on the initial conditions to generate random numbers, but it has the disadvantages of insensitivity to deterministic noise and long response time; the oscillation sampling method mainly uses D flip-flops to combine two independent The oscillating signal is mixed, but to obtain better randomness, the sampling clock is required to have a larger phase noise

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