Comparison of the techniques decision tree and MLP for data mining in SPAMs detection to computer networks

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Costa, Kelton
Ribeiro, Patricia
Camargo, Atair
Rossi, Victor
Martins, Henrique
Neves, Miguel
Fabris, Ricardo
Imaisumi, Renato
Papa, Joao Paulo [UNESP]

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Anomalies in computer networks has increased in the last decades and raised concern to create techniques to identify these unusual traffic patterns. This research aims to use data mining techniques in order to correctly identify these anomalies. Weka is a collection of machine learning algorithms for data mining tasks - was used to identify and analyse anomalies of a data set called SPAMBASE in order to improve this environment. © 2013 IEEE.



Anomalies, Artificial Neural Networks, Computer networks, Data Mining

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2013 3rd International Conference on Innovative Computing Technology, INTECH 2013, p. 344-348.