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This article aims to present the development of a Network Intrusion Detection System (NIDS), with real environment trac, using the technique of Artificial Neural Networks to classify trac as intrusion or normal. For the experiments, two databases were used: the network trac database provided by ISCX; and a test database created in real-world environment. The results obtained using the technique of Artificial Neural Networks, trained with the ISCX database, showed accuracy rates of around 90%, for the ISCX data itself, and 98% for the real environment test data. These results arm the feasibility of implementing the technique of Artificial Neural Networks to solve problems of classification of trac of computer networks.

Sistema de Detecção de Intrusão em Redes de Computadores Utilizando Redes Neurais Artificiais