Atmospheric pressure air microplasma current time series for true random bit generation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2020-12-01

AUTHORS

Anis Allagui, Sohaib Majzoub, Ahmed S. Elwakil, Andrea Espinel Rojas, Hussain Alawadhi

ABSTRACT

Generating true random bits of high quality at high data rates is usually viewed as a challenging task. To do so, physical sources of entropy with wide bandwidth are required which are able to provide truly random bits and not pseudorandom bits, as it is the case with deterministic algorithms and chaotic systems. In this work we demonstrate a reliable high-speed true random bit generator (TRBG) device based on the unpredictable electrical current time series of atmospheric pressure air microplasma (APAMP). After binarization of the sampled current time series, no further post-processing was needed in order for the bitstreams to pass all 15 tests of the NIST SP 800-22 statistical test suite. Several configurations of the system have been successfully tested at different sampling rates up to 100 MS/s, and with different inter-electrode distances giving visible/non-visible optical emissions. The cost-effectiveness, simplicity and ease of implementation of the proposed APAMP system compared to others makes it a very promising solution for portable TRBGs. More... »

PAGES

20971

References to SciGraph publications

  • 2009-12-13. An optical ultrafast random bit generator in NATURE PHOTONICS
  • 2015-02-27. Physics and applications of laser diode chaos in NATURE PHOTONICS
  • 2019-02-18. Generating randomness: making the most out of disordering a false order into a real one in JOURNAL OF TRANSLATIONAL MEDICINE
  • 2016-06-28. Quantum random number generation in NPJ QUANTUM INFORMATION
  • 2002-07-23. The development of microplasmas for spectrochemical analysis in ANALYTICAL AND BIOANALYTICAL CHEMISTRY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41598-020-77956-5

    DOI

    http://dx.doi.org/10.1038/s41598-020-77956-5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1132950389

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/33262436


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