1
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Security Enrichment in Intrusion Detection System Using Classifier Ensemble

      ,
      Journal of Electrical and Computer Engineering
      Hindawi Limited

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In the era of Internet and with increasing number of people as its end users, a large number of attack categories are introduced daily. Hence, effective detection of various attacks with the help of Intrusion Detection Systems is an emerging trend in research these days. Existing studies show effectiveness of machine learning approaches in handling Intrusion Detection Systems. In this work, we aim to enhance detection rate of Intrusion Detection System by using machine learning technique. We propose a novel classifier ensemble based IDS that is constructed using hybrid approach which combines data level and feature level approach. Classifier ensembles combine the opinions of different experts and improve the intrusion detection rate. Experimental results show the improved detection rates of our system compared to reference technique.

          Related collections

          Most cited references11

          • Record: found
          • Abstract: not found
          • Article: not found

          A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            A novel SVM-kNN-PSO ensemble method for intrusion detection system

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              AdaBoost-Based Algorithm for Network Intrusion Detection

                Bookmark

                Author and article information

                Journal
                Journal of Electrical and Computer Engineering
                Journal of Electrical and Computer Engineering
                Hindawi Limited
                2090-0147
                2090-0155
                2017
                2017
                : 2017
                :
                : 1-6
                Article
                10.1155/2017/1794849
                bdc33306-d87a-4fcd-b232-de8fb5f0c9c7
                © 2017

                http://creativecommons.org/licenses/by/4.0/

                History

                Comments

                Comment on this article