International Journal of Emerging Trends & Technology in Computer Science
A Motivation for Recent Innovation & Research
ISSN 2278-6856
www.ijettcs.org

Call for Paper, Published Articles, Indexing Infromation Data Reduction and Neural Networking Algorithms to Improve Intrusion Detection System with NSL-KDD Dataset, Authors : Y.P. Raiwani, Shailesh Singh Panwar , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), www.ijettcs.org
Volume & Issue no: Volume 4, Issue 1, January - February 2015

Title:
Data Reduction and Neural Networking Algorithms to Improve Intrusion Detection System with NSL-KDD Dataset
Author Name:
Y.P. Raiwani, Shailesh Singh Panwar
Abstract:
ABSTRACT Most of the researchers have argued that Artificial Neural Networks (ANNs) can improve the performance of intrusion detection systems (IDS). The central areas in network intrusion detection are how to build effective systems that are able to distinguish normal from intrusive traffic. In this paper we have used data reduction algorithm cfs Subset and four different neural networking algorithms namely Multilayer Perception, Stochastic Gradient Descent, Logistic Regression and Voted Perception. All these algorithms are implemented in WEKA data mining tool to evaluate the performance. For experimental work, NSL-KDD dataset is used. First we reduce data set by data reduction algorithm after this each neural based algorithm is tested with conducted dataset. The results show that the Multilayer Perception neural network algorithm is providing more accurate results than other algorithms. Keywords:-Data Mining, Intrusion Detection System, Neural Network Algorithm, NSL-KDD dataset
Cite this article:
Y.P. Raiwani, Shailesh Singh Panwar , " Data Reduction and Neural Networking Algorithms to Improve Intrusion Detection System with NSL-KDD Dataset " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 4, Issue 1, January - February 2015 , pp. 219-225 , ISSN 2278-6856.
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