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International Conference on Future Data and Security Engineering

FDSE 2017: Future Data and Security Engineering pp 381–394Cite as

Application of Rough Sets to Negative Selection Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10646))

Abstract

Immune-based algorithms are mainly used for detecting anomalies in datasets from various domains. However, one of the main areas in which they are applied is computer security. Due to increased number of victim connections, a new effective approaches still are needed. Negative Selection Algorithms seem to be very interesting as they have a unique feature which allow for detecting new type of attacks. This paper presents the possibility of applying the rough sets inspirations to improve its efficiency and deal with uncertainty and inconsistency in data.

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Notes

  1. 1.

    The universe is assumed to be finite since some formulas introduced in this paper do not hold for infinite sets, see e.g. the standard rough inclusion function.

  2. 2.

    Here, concept is understood as a subset of the universe.

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Acknowledgments

This research was partially supported by the grant S/WI/3/13 of the Polish Ministry of Science and Higher Education. I would like to thank Piotr Hońko for his valuable comments.

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Authors and Affiliations

  1. Faculty of Computer Science, Białystok University of Technology, ul. Wiejska 45a, 15-331, Białystok, Poland

    Andrzej Chmielewski

Authors
  1. Andrzej Chmielewski
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Correspondence to Andrzej Chmielewski .

Editor information

Editors and Affiliations

  1. HCMC University of Technology, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler University Linz, Linz, Austria

    Roland Wagner

  3. Johannes Kepler University Linz, Linz, Austria

    Josef Küng

  4. Ho Chi Minh City University of Technolog , Ho Chi Minh City, Vietnam

    Nam Thoai

  5. Hosei University, Koganei, Tokyo, Japan

    Makoto Takizawa

  6. University of Vienna, Vienna, Austria

    Erich J. Neuhold

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Chmielewski, A. (2017). Application of Rough Sets to Negative Selection Algorithms. In: Dang, T., Wagner, R., Küng, J., Thoai, N., Takizawa, M., Neuhold, E. (eds) Future Data and Security Engineering. FDSE 2017. Lecture Notes in Computer Science(), vol 10646. Springer, Cham. https://doi.org/10.1007/978-3-319-70004-5_27

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  • DOI: https://doi.org/10.1007/978-3-319-70004-5_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70003-8

  • Online ISBN: 978-3-319-70004-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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