Abstract
One of the most concerning problems faced by practitioners, within the development and operation of IT communication networks, is the crescent number of network intrusion attempts. That kind of attacks compromise the integrity of several services provided through the Internet. This paper presents a technique capable of optimize Danger Theory-based Intrusion Detection Systems through the use of a Genetic Algorithms. To validate the approach, tests were performed on the KDD Cup 1999 database, provided by the University of California Irvine (UCI).
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Lima Santanelli, J., de Lima Neto, F.B. (2017). Network Intrusion Detection Using Danger Theory and Genetic Algorithms. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_39
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DOI: https://doi.org/10.1007/978-3-319-53480-0_39
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