DocumentCode
2963872
Title
Spam intrusion detection in computer networks using intelligent techniques
Author
Bellin Ribeiro, Patricia ; Alexandre da Silva, Luis ; Pontara da Costa, Kelton Augusto
Author_Institution
Dept. of Comput., Coll. of Technol. of Sao Paulo State, Bauru, Brazil
fYear
2015
fDate
11-15 May 2015
Firstpage
1357
Lastpage
1360
Abstract
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, particularly in spam detection, for it was applied an collection of machine learning algorithms for data mining tasks and an dataset called SPAMBASE to identify the best techniques for this type of anomaly.
Keywords
computer network security; data mining; learning (artificial intelligence); telecommunication traffic; unsolicited e-mail; SPAMBASE dataset; computer network anomaly; data mining technique; intelligent technique; machine learning algorithm; spam intrusion detection; traffic pattern identification; Bagging; Classification algorithms; Conferences; Data mining; Decision trees; Unsolicited electronic mail; Anomalies; Artificial Neural Networks; Computer networks; Data Mining; SPAMBASE; Weka Tool;
fLanguage
English
Publisher
ieee
Conference_Titel
Integrated Network Management (IM), 2015 IFIP/IEEE International Symposium on
Conference_Location
Ottawa, ON
Type
conf
DOI
10.1109/INM.2015.7140495
Filename
7140495
Link To Document