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Reseach Article

A Case Study: Stream Data Mining Classification

Published on December 2015 by Ketan Sanjay Desale, Roshani Ade
National Conference on Advances in Computing
Foundation of Computer Science USA
NCAC2015 - Number 2
December 2015
Authors: Ketan Sanjay Desale, Roshani Ade
5a3bdbc0-8801-4feb-bc9e-74cc2a2531cd

Ketan Sanjay Desale, Roshani Ade . A Case Study: Stream Data Mining Classification. National Conference on Advances in Computing. NCAC2015, 2 (December 2015), 1-4.

@article{
author = { Ketan Sanjay Desale, Roshani Ade },
title = { A Case Study: Stream Data Mining Classification },
journal = { National Conference on Advances in Computing },
issue_date = { December 2015 },
volume = { NCAC2015 },
number = { 2 },
month = { December },
year = { 2015 },
issn = 0975-8887,
pages = { 1-4 },
numpages = 4,
url = { /proceedings/ncac2015/number2/23361-5020/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Computing
%A Ketan Sanjay Desale
%A Roshani Ade
%T A Case Study: Stream Data Mining Classification
%J National Conference on Advances in Computing
%@ 0975-8887
%V NCAC2015
%N 2
%P 1-4
%D 2015
%I International Journal of Computer Applications
Abstract

Continuous and unending growth of data created so many challenges in data mining task. Data mining is extraction meaningful information i. e. knowledge from large datasets for the future decision making. The data which is continuously generating with changing values is known as streaming data. We face many problems with streaming data as we are unable to store it and process it. Network data is one of the best examples of streaming data. Intrusion Detection System (IDS) used to detect the malicious user to protect the network. System's safety in a network is a prime important factor. In this paper, we present comprehensive approach to improve performance of IDS by applying some classification techniques with streaming dataset. For the experiment purpose we created our own network dataset which shows significant accuracy in results after applying classifiers.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Naive Bayes Hoeffding Tree Intrusion Detection System (ids)