Paper Title :Classifying Diversified Attacks In Ids Using Data Mining Techniques
Author :N.Ramakrishnan, Upasna Singh
Article Citation :N.Ramakrishnan ,Upasna Singh ,
(2014 ) " Classifying Diversified Attacks In Ids Using Data Mining Techniques " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 50-54,
Volume-2,Issue-4
Abstract : Abstract—Latest information security techniques like user authentication, antivirus, firewalls, data encryption etc fail to
prevent intrusion in any computer network. This may be attributed to the vulnerability in computer system or computer
network. There is a need to use some sophisticated security tools like Intrusion Detection System (IDS) in order to protect
our system/network. However these tools suffer from challenges posed by multi dimensionality in data. Data mining
techniques like feature extraction algorithms based on mutual information are found to be effective to negotiate these
technical challenges. The proposed approach measures mutual information through Information gain and then extracts
features from bench marked data set KDDCUP99. Further the LSSVM classifier will detect the type of attack with better
accuracy.
Type : Research paper
Published : Volume-2,Issue-4
DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-598
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Copyright: © Institute of Research and Journals
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Published on 2014-04-12 |
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