Abstract
We discuss the application of Artificial Intelligence for the design of intrusion detection systems (IDS) applied on computer networks. For this purpose, we use J48 rand Clonal-G [5] immune artificial system Algorithms, in WEKA software, with the purpose to classify and predict intrusions in KDD-Cup 1999 and Kyoto 2006 databases. We obtain for the KDD-Cup 1999 database 92.69% for ClonalG and 99.91% of precision for J48 respectively. For the Kyoto University 2006 database, we obtain 95.2% for ClonalG and 99.25% of precision for J48. Finally, based on these results we propose a model to detect intrusions using AI techniques. The main contribution of the paper is the adaptability of the CLONAL-G Algorithm and the reduction of database attributes by using Genetic Search.
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Ortuño, S.Y., Hernández Aguilar, J.A., Taboada, B., Ochoa Ortiz, C.A., Ramírez, M.P., Arroyo Figueroa, G. (2018). The Use of Artificial Intelligence for the Intrusion Detection System in Computer Networks. In: Castro, F., Miranda-Jiménez, S., González-Mendoza, M. (eds) Advances in Soft Computing. MICAI 2017. Lecture Notes in Computer Science(), vol 10632. Springer, Cham. https://doi.org/10.1007/978-3-030-02837-4_25
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