News Updates Monday 16th Jul 2018 :
  • Welcome to INPRESSCO, world's leading publishers, We have served more than 10000+ authors
  • Articles are invited in engineering, science, technology, management, industrial engg, biotechnology etc.
  • Paper submission last date of July/Aug 2018 extended to 20 July 2018, Submit online or at editor.ijcet@inpressco.com
  • Our journals are indexed in NAAS, University of Regensburg Germany, Google Scholar, Cross Ref etc.
  • DOI is given to all articles

A Hybrid Intrusion Detection System Based on C5.0 Decision Tree and One-Class SVM


Author : Meesala Shobha Rani and S. Basil Xavier

Pages : 2001-2007
Download PDF
Abstract

Cyber security threats have become increasingly sophisticated and complex. Intrusion detection which is one of the main problems in computer security has the main goal to detect infrequent access or attacks and to protect internal networks. A new hybrid intrusion detection method combining multiple classifiers for classifying anomalous and normal activities in the computer network is presented. The misuse detection model is built based on the C5.0 Decision tree algorithm and using the information collected anomaly detection model is built which is implemented by one-class Support Vector Machine (SVM). Integration of multiple algorithms helps to get better performance. The Experimental results are performed on NSL-KDD Dataset, and it is shown that overall performance of the proposed approach is improved in terms of detection rate and low false alarms rate in comparison to the existing techniques.

Keywords: Intrusion detection system, Misuse detection, Anomaly detection, hybrid approach, C5.0 Decision tree, One Class SVM.

Article published in International Journal of Current Engineering and Technology, Vol.5, No.3 (June-2015)

 

Call for Papers
  1. IJCET- July/Aug 2018 Issue

    Submission Last Date
    20 July
  2. DOI is given to all articles
  3. Current Issue
  4. IJTT-Sept-2018
  5. IJAIE-Sept-2018
  6. IJCSB-Sept-2018
  • Inpressco Google Scholar
  • Inpressco Science Central
  • Inpressco Global impact factor
  • Inpressco aap

International Press corporation is licensed under a Creative Commons Attribution-Non Commercial NoDerivs 3.0 Unported License
©2010-2018 INPRESSCO® All Rights Reserved