DocumentCode :
256196
Title :
Overview of intrusion detection using data-mining and the features selection
Author :
El Moussaid, Nadya ; Toumanari, Ahmed
Author_Institution :
Nat. Sch. of Appl. Sci., Ibno Zohr Univ., Agadir, Morocco
fYear :
2014
fDate :
14-16 April 2014
Firstpage :
1269
Lastpage :
1273
Abstract :
Most of traditional intrusion detection systems, Anomaly-Based detection and Signature-based detection, suffer from many drawbacks. This paper exposes the limits and drawback of traditional Intrusion detection systems. Consequently the main goal of this paper is to expose data mining techniques and approaches to improve the performance of the traditional intrusion detection system to identify known and unknown attack´s patterns.
Keywords :
data mining; digital signatures; anomaly-based detection; attack patterns; data-mining; features selection; intrusion detection systems; signature-based detection; Feature extraction; Probes; Classification; Data-Mining; Detection Systems (IDS); KDD; KDD Cup´99 dataset;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Computing and Systems (ICMCS), 2014 International Conference on
Conference_Location :
Marrakech
Print_ISBN :
978-1-4799-3823-0
Type :
conf
DOI :
10.1109/ICMCS.2014.6911205
Filename :
6911205
Link To Document :
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