Intrusion detection system by fuzzy interpolation

Yang, Longzhi, Li, Jie, Fehringer, Gerhard, Barraclough, Phoebe, Sexton, Graham and Cao, Yi (2017) Intrusion detection system by fuzzy interpolation. In: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): 9-12 July 2017, Naples, Italy. IEEE, Piscataway, NJ, pp. 1955-1960. ISBN 9781509060351, 9781509060344

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Official URL: https://doi.org/10.1109/FUZZ-IEEE.2017.8015710

Abstract

Network intrusion detection systems identify malicious connections and thus help protect networks from attacks. Various data-driven approaches have been used in the development of network intrusion detection systems, which usually lead to either very complex systems or poor generalization ability due to the complexity of this challenge. This paper proposes a data-driven network intrusion detection system using fuzzy interpolation in an effort to address the aforementioned limitations. In particular, the developed system equipped with a sparse rule base not only guarantees the online performance of intrusion detection, but also allows the generation of security alerts from situations which are not directly covered by the existing knowledge base. The proposed system has been applied to a well-known data set for system validation and evaluation with competitive results generated.

Item Type: Book Section
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 14 Sep 2018 10:52
Last Modified: 10 Oct 2019 14:11
URI: http://nrl.northumbria.ac.uk/id/eprint/35718

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