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Reseach Article

Big Heterogeneous Data for Intrusion Detection

Published on February 2016 by Rupali V. Molawade, Vijaya S. Waghmare
International Conference on Advances in Science and Technology
Foundation of Computer Science USA
ICAST2015 - Number 1
February 2016
Authors: Rupali V. Molawade, Vijaya S. Waghmare
26230d3b-000c-49ef-8535-36963a9c2378

Rupali V. Molawade, Vijaya S. Waghmare . Big Heterogeneous Data for Intrusion Detection. International Conference on Advances in Science and Technology. ICAST2015, 1 (February 2016), 24-27.

@article{
author = { Rupali V. Molawade, Vijaya S. Waghmare },
title = { Big Heterogeneous Data for Intrusion Detection },
journal = { International Conference on Advances in Science and Technology },
issue_date = { February 2016 },
volume = { ICAST2015 },
number = { 1 },
month = { February },
year = { 2016 },
issn = 0975-8887,
pages = { 24-27 },
numpages = 4,
url = { /proceedings/icast2015/number1/24221-3008/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Science and Technology
%A Rupali V. Molawade
%A Vijaya S. Waghmare
%T Big Heterogeneous Data for Intrusion Detection
%J International Conference on Advances in Science and Technology
%@ 0975-8887
%V ICAST2015
%N 1
%P 24-27
%D 2016
%I International Journal of Computer Applications
Abstract

Intrusion Detection has been heavily studied in both industry and academia, but cyber security analysts still desire much more alert accuracy and overall threat analysis in order to secure their systems within cyberspace. Improvements to Intrusion Detection could be achieved by embracing a more comprehensive approach in monitoring security events from many different heterogeneous sources. Correlating security events from heterogeneous sources can grant a more holistic view and greater situational awareness of cyber threats. One problem with this approach is that currently, even a single event source (e. g. , network traffic) can experience Big Data challenges when considered alone. Attempts to use more heterogeneous data sources pose an even greater Big Data challenge. Big Data technologies for Intrusion Detection can help solve these Big Heterogeneous Data challenges. In this paper, we review the scope of works considering the problem of heterogeneous data and in particular Big Heterogeneous Data

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Index Terms

Computer Science
Information Sciences

Keywords

Ids Bigdata Heterogeneity Corelation