http://repositorio.unb.br/handle/10482/11111| Fichier | Description | Taille | Format | |
|---|---|---|---|---|
| ARTIGO_DetectingAttacksComputer.pdf | 316,19 kB | Adobe PDF | Voir/Ouvrir |
| 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 |
Ce document est autorisé sous une licence de type Licence Creative Commons
