• #0 (no title)
  • #0 (no title)
  • About
  • Facebook
  • Twitter
  • RSS
(As ISO 9001:2015 Certified Publications)
    • Quick Search
    • Advanced Search
  • Home
  • Editorial Policy
  • Author Guidelines
  • Submission
  • Copyright Form
  • Career
  • Contact us
  • Subscription

Back to Journal

Home»Articles»A Data Mining Approach for Intrusion Detection in a Computer Network

JournalCover

Asian Journal of Computer Science and Technology (AJCST)

Editor Dr. K. Ganesh
Print ISSN : 2249-0701
Frequency : Quarterly

A Data Mining Approach for Intrusion Detection in a Computer Network

Author : M. Priya and M. Rajeshwari
Volume 8 No.1 Special Issue:February 2019 pp 94-97

Abstract

As activities being done on the internet keep expanding every day due to the fact that we are in the era of the information age, securing sensitive and crucial data on computer networks against malicious attacks tends to be a challenging issue. Designing effective Intrusion Detection Systems (IDSs) with maximized accuracy and low rate of false alarms is an imperative need in the world of cyber-attacks. This work was designed to employ an ensemble data mining technique for improving IDSs by carrying out some experiments using the KDD 99 intrusion dataset. Dataset was fragmented into five, representing the major categories of attacks: Normal, DOS (Denial of Service), Probing (Information gathering), R2L (Remote to Local) and U2R (User to Root). An ensemble classifier using the Stacking method with the Naïve Bayes and Multilayer perceptron algorithms as the base classifiers and J48 as the meta learner was developed. The base classifiers were also employed on the dataset individually, and performance comparison was done between individual classifiers and the ensemble classifier. A 10-fold cross validation for training and testing of data and Gain ratio technique for filtering of the dataset was adopted. Ensemble classifier maximized accuracy the most and helped in reduction of false positives of the U2R attack type.

Keywords

Intrusion Detection System, Ensemble, Stacking, Network Attacks, Data Mining

Full Text:

References

[1] R. C. Summers, 1997, “Secure computing: threats and safeguards”, New York: McGraw Hill:
[2] A. Mounji, “Languages and Tools for Rule Based Distributed Intrusion Detection”, PhD Thesis, Faculties Universalities Notre-Dame delaPaix Namur, 1997.
[3] G. V. Nadiammai, S. Krishaveni, M. Hemalatha, “A comprehensive Analysis and study in intrusion detection system using data mining Techniques”, IJCA, Vol. 35, No. 8, 2011.
[4] A. Youssef and A. Emam, “Network intrusion detection using data mining and network behavior”, International Journal of Computer Science & Information Technology, IJCSIT, Vol. 3, No. 6, 2011.
[5] Iwan, Syarif Ed, Zaluska, Adam Prugel-Bennett, Gary Wills, “Application of Bagging, Boosting and Stacking to Intrusion Detection”, School of Electronics and Computer Science, University of Southampton, UK, 2012.
[6] H. Zhao, “Intrusion Detection Ensemble Algorithm based on Bagging and Neighbourhood Rough Set”, International Journal of Security and Its Applications Vol. 7, No. 5 pp.193-204, 2014.
[7] T Subbulakshmi, A Ramamoorthi, and S. M. Shalinie, “Ensemble design for intrusion detection systems”, International Journal of Computer science & Information Technology, IJCSIT, Vol. 1, No 1, 2009.
[8] S Singh and Sanjay, “An ensemble approaches for feature selection of Cyber Attack Dataset”, International Journal of Computer Science and Information Security IJCSIS, Vol. 6, No. 2, 2009.
[9] A. Borji, “Combining Heterogeneous Classifiers for Network Intrusion Detection”, Cervesato, Ed. ASIAN 2007, LNCS 4846, pp. 254-260 © Springer-VerlagBerlin Heidelberg, 2007.
[10] M. Govindarajan and R. M. Chandrasekaran, “Intrusion Detection using an Ensemble of Classification Methods”, Proceedings of the World Congress on Engineering and Computer Science, San Francisco, USA, WCECS, Vol. 1, October 24-26 2012.
[11] H Ibrahim, M. Badr, A. Shaheen, “Adaptive Layered Approach using Machine Learning Techniques with Gain Ratio for Intrusion Detection Systems”, International Journal of Computer Applications, Vol.56, No. 7, 2012.
[12] Yimin Wu, “High –dimensional Pattern Analysis in Multimedia Information Retrieval and Bioinformatics”, Doctoral Thesis, State University of New York, January 2004.

Asian Journal of Computer Science and Technology is a peer-reviewed international journal that publishes high-quality scientific articles (both theory and practice) and research papers covering all aspects of future computer and Information Technology areas. Topics include, but are not limited to:

Foundations of High-performance ComputingTheory of algorithms and computability

Parallel & distributed computing

Computer networks

Neural networks

LAN/WAN/MAN

Database theory & practice

Mobile Computing for e-Commerce

Future Internet architecture

Protocols and services

Mobile and ubiquitous networks

Green networking

Internet content search

Opportunistic networking

Network applications

Network scaling and limits

Artifial Intelligences

Pattern/Image Recognitions

Communication Network

Information Security

Knowledge Management

Management Information systems

Multimedia communicatiions

Operations research

Optical networks

Software Engineering

Virtual reality

Web Technologies

Wireless technology

As activities being done on the internet keep expanding every day due to the fact that we are in the era of the information age, securing sensitive and crucial data on computer networks against malicious attacks tends to be a challenging issue. Designing effective Intrusion Detection Systems (IDSs) with maximized accuracy and low rate of false alarms is an imperative need in the world of cyber-attacks. This work was designed to employ an ensemble data mining technique for improving IDSs by carrying out some experiments using the KDD 99 intrusion dataset. Dataset was fragmented into five, representing the major categories of attacks: Normal, DOS (Denial of Service), Probing (Information gathering), R2L (Remote to Local) and U2R (User to Root). An ensemble classifier using the Stacking method with the Naïve Bayes and Multilayer perceptron algorithms as the base classifiers and J48 as the meta learner was developed. The base classifiers were also employed on the dataset individually, and performance comparison was done between individual classifiers and the ensemble classifier. A 10-fold cross validation for training and testing of data and Gain ratio technique for filtering of the dataset was adopted. Ensemble classifier maximized accuracy the most and helped in reduction of false positives of the U2R attack type.

Editor-in-Chief
Dr. K. Ganesh
Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
Expert at McKinsey and Company, India
[email protected]
Editorial Advisory Board
Dr. Eng. Hamid Ali Abed AL-Asadi
Department of Computer Science, Basra University, Iraq
[email protected]
Dr. Norjihan Binti Abdul Ghani
Department of Information System, University of Malaya, Malaysia
[email protected]
Dr. Christos Bouras
Department of Computer Engineering & Informatics, University of Patras, Greece
[email protected]
Dr. Maizatul Akmar Binti Ismail
Department of Information System, University of Malaya, Malaysia
[email protected]
Dr. Harold Castro
Department of Systems Engineering and Computing, University of the Andes, Colombia
[email protected]
Dr. Busyairah Binti Syd Ali
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. Sri Devi Ravana
Department of Information system, University of Malaya, Malaysia
[email protected]
Dr. Karpaga Selvi Subramanian
Department of Computer Engineering, Mekelle University, Ethiopia
[email protected]
Dr. Mazliza Binti Othman
Department of Computer System & Technology, University of Malaya, Malaysia
[email protected]
Dr. Chiam Yin Kia
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. OUH Eng Lieh
Department of Information Systems, Singapore Management University, Singapore
[email protected]

2016

2015

2014

  • Results
  • Asian Review of Mechanical Engineering (ARME)
  • career

2013

  • Home
  • Shop
  • My Account
  • Logout
  • Contact us
  • The Asian Review of Civil Engineering (TARCE)

2012

  • Asian Journal of Electrical Sciences(AJES)
  • Asian Journal of Computer Science and Technology (AJCST)
  • Asian Journal of Information Science and Technology (AJIST)
  • Asian Journal of Engineering and Applied Technology (AJEAT)
  • Asian Journal of Science and Applied Technology (AJSAT)
  • Asian Journal of Managerial Science (AJMS)
  • Asian Review of Social Sciences (ARSS)

2011

2010

    Table of Contents

    Editorial Note

    Editorial Dr. K. Ganesh

    Editor-in-Chief
    Dr. K. Ganesh
    Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
    Expert at McKinsey and Company, India
    [email protected]
    Editorial Advisory Board
    Dr. Eng. Hamid Ali Abed AL-Asadi
    Department of Computer Science, Basra University, Iraq
    [email protected]
    Dr. Norjihan Binti Abdul Ghani
    Department of Information System, University of Malaya, Malaysia
    [email protected]
    Dr. Christos Bouras
    Department of Computer Engineering & Informatics, University of Patras, Greece
    [email protected]
    Dr. Maizatul Akmar Binti Ismail
    Department of Information System, University of Malaya, Malaysia
    [email protected]
    Dr. Harold Castro
    Department of Systems Engineering and Computing, University of the Andes, Colombia
    [email protected]
    Dr. Busyairah Binti Syd Ali
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. Sri Devi Ravana
    Department of Information system, University of Malaya, Malaysia
    [email protected]
    Dr. Karpaga Selvi Subramanian
    Department of Computer Engineering, Mekelle University, Ethiopia
    [email protected]
    Dr. Mazliza Binti Othman
    Department of Computer System & Technology, University of Malaya, Malaysia
    [email protected]
    Dr. Chiam Yin Kia
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. OUH Eng Lieh
    Department of Information Systems, Singapore Management University, Singapore
    [email protected]

    Articles

Advanced Search

You can submit your research paper to the journal in just a few clicks. Please follow the steps outlined below: 1. Register your details and select to be an Author 2. Log in with your user name and password 3. ‘Start a new submission’ and follow these 5 steps:

[gravityform id="1" name="Registration" title="false" description="false"]

Privacy Statement

The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.

Privacy Statement

The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.

Lorem1 ipsum dolor sit amet, consectetur adipiscing elit. Nulla convallis ultricies scelerisque. Fusce dolor augue, sollicitudin eget lacus vitae, rutrum commodo lacus. Praesent ullamcorper facilisis dui. Sed suscipit id lorem ut dapibus. Integer dictum cursus nisl, quis ullamcorper augue. Sed non rutrum mauris. Maecenas in dolor est. Donec eget sagittis mi. Sed non leo eu odio mollis pulvinar vitae et leo. Integer eu feugiat tortor. Duis massa purus, eleifend id erat eget, hendrerit semper risus. Suspendisse cursus varius dapibus

Lorem1 ipsum dolor sit amet, consectetur adipiscing elit. Nulla convallis ultricies scelerisque. Fusce dolor augue, sollicitudin eget lacus vitae, rutrum commodo lacus. Praesent ullamcorper facilisis dui. Sed suscipit id lorem ut dapibus. Integer dictum cursus nisl, quis ullamcorper augue.

Subscription

Subscription (for 12 issues):
Rs. 5000; Overseas - USD 500;
Cheque drawn in favour of "Informatics Publishing Limited"
Click here to download online subscription form

Download

DD Mailing Address

Lorem1 ipsum dolor sit amet,
Lorem1 ipsum dolor sit amet,
Lorem1 ipsum dolor sit amet.

BACK TO TOP

Outstanding Scholars

The Journals honor Outstanding Scholars in various fields. Scholar of the Month should have contributed to their field and to the larger community. Recipients will be nominated by the Advisory Board and approved by the Editor-in-Chief of the allied journals published by The Research Publication. Scholar of the Month will be displayed in the web portal of the concerned journal.

Please send your brief write up to [email protected]

Editors and Reviewers

The Research Publication is seeking qualified researchers to join its editorial team as Associate Editor, Editorial Advisory Board Member, and Reviewers.
Kindly send your details to [email protected]

Call For Papers

Authors are requested to submit their papers electronically to [email protected] with mentioning the journal title.

Mailing Address

The Research Publication 1/611, Maruthi Nagar, Rakkipalayam Post, Coimbatore – 641 031, Tamil Nadu, India Phone No.: 0422 2461001

  • About
  • Editorial Policy
  • Author Guidelines
  • Contact us
  • Copyright
  • Facebook
  • Twitter
  • RSS

© 2015 The Research Publication. All rights reserved.

The Research Publication
  • Home
  • Editorial Policy
  • Author Guidelines
  • Submission
  • Copyright Form
  • Career
  • Contact us
  • Subscription