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Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection

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  • Rafał Kozik
  • Marek Pawlicki
  • Michał Choraś
  • Witold Pedrycz

Abstract

Network and information security are regarded as some of the most pressing problems of contemporary economy, affecting both individual citizens and entire societies, making them a highlight for homeland security. Innovative approaches to handle this challenge are undertaken by the scientific community, proposing the utilization of the emerging, advanced machine learning methods. This very paper puts forward a novel approach to the detection of cyberattacks taking inventory of the practical application of information granules. The feasibility of utilizing Granular Computing (GC) as a solution to the most current challenges in cybersecurity is researched. To the best of our knowledge, granular computing has not yet been widely examined or used for cybersecurity application purposes. The major contribution of this work is a method for constructing information granules from network data. We then report promising results on a benchmark dataset.

Suggested Citation

  • Rafał Kozik & Marek Pawlicki & Michał Choraś & Witold Pedrycz, 2019. "Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection," Complexity, Hindawi, vol. 2019, pages 1-9, January.
    • Handle: RePEc:hin:complx:5826737
    DOI: 10.1155/2019/5826737
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    References listed on IDEAS

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    1. Huang, Bing & Zhuang, Yu-liang & Li, Hua-xiong, 2013. "Information granulation and uncertainty measures in interval-valued intuitionistic fuzzy information systems," European Journal of Operational Research, Elsevier, vol. 231(1), pages 162-170.
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    Cited by:

    1. Shen Yan & Sing Kiong Nguang & Liruo Zhang, 2019. "Nonfragile Integral-Based Event-Triggered Control of Uncertain Cyber-Physical Systems under Cyber‐Attacks," Complexity, Hindawi, vol. 2019, pages 1-14, November.

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