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Random Forest in Whitelist-Based ATM Security

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Intelligent Information and Database Systems (ACIIDS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13758))

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Abstract

Accelerated by the COVID-19 pandemic, the trend of highly-sophisticated logical attacks on Automated Teller Machines (ATMs) is ever-increasing nowadays. Due to the nature of attacks, it is common to use zero-day protection for the devices. The most secure solutions available are using whitelist-based policies, which are extremely hard to configure. This article presents the concept of a semi-supervised decision support system based on the Random forest algorithm for generating a whitelist-based security policy using the ATM usage data. The obtained results confirm that the Random forest algorithm is effective in such scenarios and can be used to increase the security of the ATMs.

Supported by Diebold Nixodrf.

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Author information

Authors and Affiliations

  1. Software Security Group, Diebold Nixdorf, Katowice, Poland

    Michal Maliszewski

  2. Institute of Computer Science, University of Silesia, Sosnowiec, Poland

    Urszula Boryczka

Authors
  1. Michal Maliszewski
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  2. Urszula Boryczka
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Corresponding author

Correspondence to Michal Maliszewski .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Vietnam National University, Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Tien Khoa Tran

  3. Al-Farabi Kazakh National University, Almaty, Kazakhstan

    Ualsher Tukayev

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  6. University of Newcastle, Newcastle, NSW, Australia

    Edward Szczerbicki

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Maliszewski, M., Boryczka, U. (2022). Random Forest in Whitelist-Based ATM Security. In: Nguyen, N.T., Tran, T.K., Tukayev, U., Hong, TP., Trawiński, B., Szczerbicki, E. (eds) Intelligent Information and Database Systems. ACIIDS 2022. Lecture Notes in Computer Science(), vol 13758. Springer, Cham. https://doi.org/10.1007/978-3-031-21967-2_24

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  • DOI: https://doi.org/10.1007/978-3-031-21967-2_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21966-5

  • Online ISBN: 978-3-031-21967-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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