True random number generator using comparator to resist periodic noise

Abstract

The invention discloses a true random number generator using comparator to resist periodic noise. The device comprises a thermal noise inverter, a differential comparator, a constant voltage source, aconfigurable flexible amplifier, a feedback unit and a D flip-flop. The positive input end and the negative input end of the differential comparator are short-circuited to enable the differential comparator to work in a common mode so as to resist power ripples and periodic noise; the node thermal noise at the output end of the thermal noise inverter in the metastable state and the thermal noiseat the short circuit node of the positive input end and the negative input end of the differential comparator in the common mode are superposed; the signal is converted into logic 1 or logic 0 throughthe configurable sensitive amplifier, and then the logic 1 or logic 0 is sampled by the D trigger to generate random sequence serial output. The feedback unit performs feedback adjustment on the configurable sensitive amplifier according to the output sequence bias to compensate environment change and process deviation. The method has the advantages of high output sequence randomness, low power consumption and less occupied chip I / O resources.

Description

technical field [0001] The invention relates to a true random number generator, in particular to a true random number generator using a comparator to resist periodic noise and using a comparator to resist periodic noise. Background technique [0002] With the rapid development of the Internet of Things, the requirements for information security are getting higher and higher, and high-entropy random number generators, as an important part of information security, have received more and more attention. Random number generators can be divided into two categories: pseudo random number generator (Pseudo Random Number Generator, PRNG) and true random number generator (True Random Number Generator, TRNG). Although the output sequence generated by the pseudo-random number generator with a specific algorithm has excellent statistical characteristics, it has the disadvantages of determinism and predictability, and is not suitable for information security. True random number generator...

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Problems solved by technology

[0004] However, the above-mentioned true random number generator has the following problems: 1. The noise amplitude at the output end of the bias circuit is small, and it is difficult to be effectively used, resulting in random sequence randomness Second, the second-stage single-ended output amplifier of the comparator needs to provide a large current in order to achieve high bandwidth, resulting in waste of power consumption; Third, the Slicer structure requires manual adjustment, which takes up more chip I / O resources

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