A method and device for generating true random numbers

Abstract

The invention relates to a method and a device for generating a true random number. The device comprises a high frequency oscillator, an initial seed number generation unit, an error diffusion calculation unit, a linear feedback unit, a control unit and a random number output unit, wherein the output end of the high frequency oscillator is connected with the input end of the initial seed number generation unit; the output end of the initial seed number generation unit is connected with the input end of the error diffusion calculation unit; the output end of the error diffusion calculation unit is connected with the linear feedback unit; the output end of the linear feedback unit is connected with the control unit; and the control unit is connected with the random number output unit. The device achieves a metastable state circuit only by using general logic hardware, so the hardware structure is simplified; one-time-pad is realized by storing an initial seed number in a cache reset at each time; judgment and feedback control are realized by using a generator polynomial; and a secure hash algorithm is realized by using an error diffusion process, therefore, an effect that the random number is difficult to copy or forecast is achieved.

Description

technical field [0001] The invention relates to the technical field of security encryption, in particular to a method and device for generating a true random number. Background technique [0002] Random numbers are an important tool for the system to encrypt, for example, the system uses random numbers to generate keys, so random number generators are an essential part of all encryption systems. A random number generator must be sufficiently secure against external or internal attacks. [0003] A random number generator should meet the following three most basic security principles: [0004] 1) Frequency and run length randomness, the output of the generator must be random, satisfy the frequency test and run length test, and ensure security against long run length and spying attacks; [0005] 2) Refactoring recovery / forward security, even if you know the state of the generator at a certain moment, you cannot infer the number of outputs of the generator before that moment; ...

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Problems solved by technology

[0005] 2) Refactoring recovery / forward security, even if you know the state of the generator at a certain moment, you cannot infer the number of outputs of the generator before that moment;

[0006] 3) Intrusion prediction / backward security, even if the state of the generator at a specific moment is known, the output of the generator after this moment cannot be inferred

[0007] The real hardware random number generator is completely different from the pseudo-random number generator. The latter is easy to implement in software and can obtain statistical random numbers; To the algorithm random number sequence is not repeatable

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