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Titre: Detecting attacks to computer networks using a multi-layer perceptron artificial neural network
Auteur(s): Amaral, Dino Macedo
Araújo, Genival Mariano de
Romariz, Alexandre Ricardo Soares
Assunto:: Redes de computação - medidas de segurança
Redes neurais (Computação)
Redes de informação - sistemas de segurança
Date de publication: 2011
Editeur: The International Journal of Forensic Computer Science
Référence bibliographique: AMARAL, Dino Macedo; ARAÚJO, Genival Mariano de; ROMARIZ, Alexandre Ricardo Soares. Detecting attacks to computer networks using a multi-layer perceptron artificial neural network. The International Journal of Forensic Computer Science, v. 3, n. 1, p. 70-74, 2011. Disponível em: <http://www.ijofcs.org/V03N1-P07%20-%20Detecting%20Attacks%20to%20Computer%20Networks.pdf>. Acesso em: 19 jun. 2012.
Résumé: In this paper, we present concepts in artificial neural networks (ANN) to help detect intrusion attacks against network computers, and introduce and compare a multi-layer perceptron ANN (MLPANN) with Snort, an open-source tool for intrusion detection systems (IDS). To conduct these comparison experiments, we inserted malicious traffic into the MLPANN to train our ANN, with results indicating that our ANN detected 99% of these input attacks.
Licença:: Disponível sob Licença Creative Commons 3.0, que permite copiar, distribuir e transmitir o trabalho, desde que seja citado o autor e licenciante. Não permite o uso para fins comerciais nem a adaptação desta.
DOI: https://dx.doi.org/10.5769/J200801007
Collection(s) :Artigos publicados em periódicos e afins

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