Exploring true random number generators Build on commercial-off-the-shelve Components

Detta är en M1-uppsats från Malmö universitet/Institutionen för datavetenskap och medieteknik (DVMT)

Sammanfattning: Generating random numbers can be accomplished through various methods, with the primary distinction lying between pseudo-random number generators (PRNGs), which are commonly used for applications that require a large amount of random data, and true random number generators (TRNGs), which are commonly used for applications that need security and unpredictability. This thesis explores the feasibility of harnessing frequency variations in the electrical grid as a source of entropy for a TRNG. By employing an iterative approach, the study has substantiated the likelihood that frequency fluctuations can serve as a reliable source of ran-domness for a TRNG. This assertion is supported by statistical testing using the comprehensive RNG testing suite known as DieHarder, where the final implementation of the TRNG yielded favourable outcomes. Nevertheless, it is worth noting that the artefact exhibited weaker resultson three specific tests within the suite, which can likely be attributed to a limited amount of generated data. Despite these limitations, the findings are undeniably promising, and futurere search endeavours should focus primarily on enhancing the generation speed of the TRNG. By doing so, it is anticipated that improved performance on the DieHarder suite and similar RNG testing suites can be achieved.

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