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Analytical Study of Different Classification Technique for KDD Cup Data'99

Riti Lath, Manish Shrivastava Published in Artificial Intelligence

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
10.5120/ijais12-450537
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  1. Riti Lath and Manish Shrivastava. Article: Analytical Study of Different Classification Technique for KDD Cup Data’99. International Journal of Applied Information Systems 3(6):5-9, July 2012. BibTeX

    @article{key:article,
    	author = "Riti Lath and Manish Shrivastava",
    	title = "Article: Analytical Study of Different Classification Technique for KDD Cup Data’99",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 3,
    	number = 6,
    	pages = "5-9",
    	month = "July",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

This paper is a concise analysis of classification of 10% of kdd cup'99 datasets based on intrusion detection. Analysis of data is performed using different techniques i. e. k-mean which is based on clustering, and k-nearest neighbor, support vector machine are classification techniques. Firstly the flat results are analyzed then preprocessed data is used. For preprocessing statistical normalization has been used. For analysis only two groups are considered that are normal and abnormal, no further division of abnormal category has been done. Matlab is used as a tool. As a result classification technique proves good in classifying data, abnormal data separately and normal and abnormal data collectively, for classification potentiality.

Reference

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Keywords

classification technique, clustering, normalization, SVM