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Random number generator using multiple entropy sources and method for generating random numbers

A random number generator, generator technology, applied in random number generators, electrical digital data processing, digital data processing components, etc., can solve problems such as difficulty in providing randomness

Pending Publication Date: 2020-11-20
NXP BV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

DRNGs may struggle to provide sufficient randomness to support the security requirements of secure applications

Method used

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  • Random number generator using multiple entropy sources and method for generating random numbers
  • Random number generator using multiple entropy sources and method for generating random numbers
  • Random number generator using multiple entropy sources and method for generating random numbers

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Embodiment Construction

[0050] Typically, random number generators (RNG) are provided, including a true random number generator (TRNG) and at least one deterministic random number generator (DRNG). Outputs of the TRNG and at least one DRNG are coupled to inputs of an exclusive OR logic function. Each of the at least one DRNG is coupled to receive a seed value from an entropy source that is separate and independent of the TRNG and any other DRNG's entropy source. In one embodiment, a static random access memory (SRAM) array is used as the source of entropy and provides the seed value. For example, in one embodiment, the source of entropy is non-overlapping segments of memory cells of an SRAM array. In another embodiment, the SRAM segments can be from separate arrays. The seed value is generated by the SRAM array at power-up. The output of the TRNG and the output of each DRNG are coupled to the input of an exclusive OR logic function. In response, the XOR logic function provides a random number.

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Abstract

A device for providing a random number generator is provided. The device may include a true random number generator, at least one deterministic random number generator, and an exclusive OR logic function. The TRNG has an output and the at least one DRNG has an output. The exclusive OR logic function has a first input coupled to the output of the TRNG and a second input coupled to the output of theat least one DRNG, and an output for providing a random number. The TRNG and the at least one DRNG may include separate and independent entropy sources. A method for generating a random number is also provided.

Description

technical field [0001] The present disclosure relates generally to random number generation, and more particularly, to random number generators and methods for generating random numbers using multiple sources of entropy. Background technique [0002] Random number generation is important to almost all secure systems. There are generally two main types of random number generators, true random number generators and pseudo random number generators. A true random number generator (TRNG) can use a source of entropy, such as thermal noise from an integrated circuit or the decay of radioactive material, to generate a stream of random numbers. One type of pseudorandom number generator, called a deterministic random number generator (DRNG), uses an algorithm to generate random numbers. Some DRNGs also include an entropy source to provide a random seed from which random numbers are generated. A seed may consist of a finite sequence of bit strings. DRNGs may struggle to provide suf...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F7/58
CPCG06F7/588H04L9/0869
Inventor 布鲁斯·默里马里奥·兰贝格尔
Owner NXP BV