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Generation of Pseudo-random Numbers Based on Network Traffic

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Advances in Soft Computing (MICAI 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12468))

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Abstract

The Pseudo Random Numbers generators can be based on chaotic maps; they are still deterministic functions, so it is possible to predict future results. On the other hand, we have the real random number generators that comply with the mentioned characteristics, this is possible at the cost of high latency and slowness by the use of physical processes. In this article, the use of network traffic in the generation of random sequences is tested. An equation is used to improve the statistical properties of the method. It is verified that network traffic tends to be more chaotic in spaces with a larger number of users. Results show that the method generates very different sequences, but with unequal bit generation. We present a method for the generation of pseudo random numbers based on network traffic, minimizing the repetition of generated sequences.

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Authors and Affiliations

  1. Universidad Católica San Pablo, Arequipa, Peru

    Wilbert Marroquin & Julio Santisteban

Authors
  1. Wilbert Marroquin
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  2. Julio Santisteban
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Corresponding author

Correspondence to Julio Santisteban .

Editor information

Editors and Affiliations

  1. Facultad de Ingeniería, Universidad Panamericana, Mexico City, Mexico

    Lourdes Martínez-Villaseñor

  2. Universidad Autónoma Metropolitana, Mexico City, Mexico

    Oscar Herrera-Alcántara

  3. Facultad de Ingeniería, Universidad Panamericana, Mexico City, Mexico

    Hiram Ponce

  4. Universidad Autónoma del Estado de Hidalgo, Hidalgo, Mexico

    Félix A. Castro-Espinoza

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Marroquin, W., Santisteban, J. (2020). Generation of Pseudo-random Numbers Based on Network Traffic. In: Martínez-Villaseñor, L., Herrera-Alcántara, O., Ponce, H., Castro-Espinoza, F.A. (eds) Advances in Soft Computing. MICAI 2020. Lecture Notes in Computer Science(), vol 12468. Springer, Cham. https://doi.org/10.1007/978-3-030-60884-2_37

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  • DOI: https://doi.org/10.1007/978-3-030-60884-2_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60883-5

  • Online ISBN: 978-3-030-60884-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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