Title :
Classification of Attacks Using Support Vector Machine (SVM) on KDDCUP´99 IDS Database
Author :
Manjiri V. Kotpalliwar;Rakhi Wajgi
Author_Institution :
Dept. of Comput. Sci. &
fDate :
4/1/2015 12:00:00 AM
Abstract :
Intrusion Detection System (IDS) is used to preserve the data integrity and confidentiality from attacks. In order to identify the type of attack in IDS, different methodologies like various data mining techniques exist. But some are very time consuming and laborious. Therefore we have proposed the usage of SVM (Support Vector Machine) for classification of attack from large amount of raw intrusion detection datasets on standard personal computers. SVM is a method which is used in data mining to extract predicted data. We have use KDDCUP´99 IDS database for classification.
Keywords :
"Support vector machines","Intrusion detection","Data mining","Accuracy","Databases","Classification algorithms","Computer science"
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2015 Fifth International Conference on
DOI :
10.1109/CSNT.2015.185