{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T14:18:10Z","timestamp":1769350690531,"version":"3.49.0"},"reference-count":36,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2017]]},"DOI":"10.1587\/transinf.2016icp0018","type":"journal-article","created":{"date-parts":[[2017,7,31]],"date-time":"2017-07-31T22:19:44Z","timestamp":1501539584000},"page":"1729-1737","source":"Crossref","is-referenced-by-count":22,"title":["HFSTE: Hybrid Feature Selections and Tree-Based Classifiers Ensemble for Intrusion Detection System"],"prefix":"10.1587","volume":"E100.D","author":[{"given":"Bayu Adhi","family":"TAMA","sequence":"first","affiliation":[{"name":"Faculty of Computer Science, University of Sriwijaya"},{"name":"Laboratory of Information Security and Internet Applications (LISIA), Dept. of IT Convergence and Application Engineering, Pukyong National University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyung-Hyune","family":"RHEE","sequence":"additional","affiliation":[{"name":"Laboratory of Information Security and Internet Applications (LISIA), Dept. of IT Convergence and Application Engineering, Pukyong National University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"[1] B.A. Tama and K.H. Rhee, \u201cPerformance analysis of multiple classifier system in DoS attack detection,\u201d International Workshop on Information Security Applications, pp.339-347, 2015.","DOI":"10.1007\/978-3-319-31875-2_28"},{"key":"2","unstructured":"[2] B.A. Tama and K.H. Rhee, \u201cData mining techniques in DoS\/DDoS attack detection: A literature review,\u201d Information (Japan), vol.18, no.8, p.3739, 2015."},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] X.-S. Gan, J.-S. Duanmu, J.-F. Wang, and W. Cong, \u201cAnomaly intrusion detection based on PLS feature extraction and core vector machine,\u201d Knowledge-Based Systems, vol.40, pp.1-6, 2013. 10.1016\/j.knosys.2012.09.004","DOI":"10.1016\/j.knosys.2012.09.004"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] B.A. Tama and K.H. Rhee, \u201cA combination of PSO-based feature selection and tree-based classifiers ensemble for intrusion detection systems,\u201d in Advances in Computer Science and Ubiquitous Computing, vol.373, pp.489-495, Springer, 2015. 10.1007\/978-981-10-0281-6_71","DOI":"10.1007\/978-981-10-0281-6_71"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] S. Mukkamala, A.H. Sung, and A. Abraham, \u201cIntrusion detection using an ensemble of intelligent paradigms,\u201d J. Netw. Comput. Appl., vol.28, no.2, pp.167-182, 2005. 10.1016\/j.jnca.2004.01.003","DOI":"10.1016\/j.jnca.2004.01.003"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] S. Peddabachigari, A. Abraham, C. Grosan, and J. Thomas, \u201cModeling intrusion detection system using hybrid intelligent systems,\u201d J. Netw. Comput. Appl., vol.30, no.1, pp.114-132, 2007. 10.1016\/j.jnca.2005.06.003","DOI":"10.1016\/j.jnca.2005.06.003"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] W. Hu, W. Hu, and S. Maybank, \u201cAdaboost-based algorithm for network intrusion detection,\u201d IEEE Trans. Syst., Man, Cybern. B, Cybernetics, vol.38, no.2, pp.577-583, 2008. 10.1109\/tsmcb.2007.914695","DOI":"10.1109\/TSMCB.2007.914695"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] J.B.D. Cabrera, C. Guti\u00e9rrez, and R.K. Mehra, \u201cEnsemble methods for anomaly detection and distributed intrusion detection in mobile ad-hoc networks,\u201d Information Fusion, vol.9, no.1, pp.96-119, 2008. 10.1016\/j.inffus.2007.03.001","DOI":"10.1016\/j.inffus.2007.03.001"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] G. Giacinto, R. Perdisci, M.D. Rio, and F. Roli, \u201cIntrusion detection in computer networks by a modular ensemble of one-class classifiers,\u201d Information Fusion, vol.9, no.1, pp.69-82, 2008. 10.1016\/j.inffus.2006.10.002","DOI":"10.1016\/j.inffus.2006.10.002"},{"key":"10","doi-asserted-by":"publisher","unstructured":"[10] M. Govindarajan and R. Chandrasekaran, \u201cIntrusion detection using neural based hybrid classification methods,\u201d Computer Networks, vol.55, no.8, pp.1662-1671, 2011. 10.1016\/j.comnet.2010.12.008","DOI":"10.1016\/j.comnet.2010.12.008"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] S.S.S. Sindhu, S. Geetha, and A. Kannan, \u201cDecision tree based light weight intrusion detection using a wrapper approach,\u201d Expert. Syst. Appl., vol.39, no.1, pp.129-141, 2012. 10.1016\/j.eswa.2011.06.013","DOI":"10.1016\/j.eswa.2011.06.013"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] J. Kevric, S. Jukic, and A. Subasi, \u201cAn effective combining classifier approach using tree algorithms for network intrusion detection,\u201d Neural Computing and Applications, pp.1-8, 2016. 10.1007\/s00521-016-2418-1","DOI":"10.1007\/s00521-016-2418-1"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[13] C.-C. Chang and C.-J. Lin, \u201cLIBSVM: A library for support vector machines,\u201d ACM Transactions on Intelligent Systems and Technology (TIST), vol.2, no.3, pp.1-27, 2011. 10.1145\/1961189.1961199","DOI":"10.1145\/1961189.1961199"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] M. Tavallaee, E. Bagheri, W. Lu, and A.A. Ghorbani, \u201cA detailed analysis of the KDD CUP 99 data set,\u201d The Second IEEE Symposium on Computational Intelligence for Security and Defence Applications 2009, pp.1-6, 2009. 10.1109\/cisda.2009.5356528","DOI":"10.1109\/CISDA.2009.5356528"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] J. Kennedy and R.C. Eberhart, \u201cA discrete binary version of the particle swarm algorithm,\u201d IEEE International Conference on Systems, Man, and Cybernetics-Computational Cybernetics and Simulation, pp.4104-4108, IEEE, 1997. 10.1109\/icsmc.1997.637339","DOI":"10.1109\/ICSMC.1997.637339"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] E. Bonabeau, M. Dorigo, and G. Theraulaz, Swarm intelligence: from natural to artificial systems, Oxford University Press, 1999.","DOI":"10.1093\/oso\/9780195131581.001.0001"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] M. Mitchell, An introduction to genetic algorithms, MIT Press, 1998.","DOI":"10.7551\/mitpress\/3927.001.0001"},{"key":"18","doi-asserted-by":"publisher","unstructured":"[18] L. Breiman, \u201cRandom forests,\u201d Machine learning, vol.45, no.1, pp.5-32, 2001. 10.1023\/a:1010933404324","DOI":"10.1023\/A:1010933404324"},{"key":"19","unstructured":"[19] R. Kohavi, \u201cScaling up the accuracy of Naive-Bayes classifiers: A decision-tree hybrid,\u201d KDD, pp.202-207, Citeseer, 1996."},{"key":"20","doi-asserted-by":"publisher","unstructured":"[20] N. Landwehr, M. Hall, and E. Frank, \u201cLogistic model trees,\u201d Machine Learning, vol.59, no.1-2, pp.161-205, 2005. 10.1007\/s10994-005-0466-3","DOI":"10.1007\/s10994-005-0466-3"},{"key":"21","doi-asserted-by":"publisher","unstructured":"[21] J.R. Quinlan, \u201cSimplifying decision trees,\u201d International Journal of Human-Computer Studies, vol.51, no.2, pp.497-510, 1999. 10.1006\/ijhc.1987.0321","DOI":"10.1006\/ijhc.1987.0321"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[22] L. Kuncheva, Combining pattern classifiers: methods and algorithms 2nd edition, John Wiley &amp; Sons, 2014.","DOI":"10.1002\/9781118914564"},{"key":"23","doi-asserted-by":"publisher","unstructured":"[23] M. Friedman, \u201cA comparison of alternative tests of significance for the problem of m rankings,\u201d The Annals of Mathematical Statistics, vol.11, no.1, pp.86-92, 1940. 10.1214\/aoms\/1177731944","DOI":"10.1214\/aoms\/1177731944"},{"key":"24","unstructured":"[24] P. Nemenyi, \u201cDistribution-free multiple comparisons,\u201d Biometrics, p.263, 1962."},{"key":"25","unstructured":"[25] M.A. Hall, Correlation-based feature selection for machine learning, Ph.D. thesis, The University of Waikato, 1999."},{"key":"26","doi-asserted-by":"publisher","unstructured":"[26] R. Jensen and Q. Shen, \u201cFuzzy-rough data reduction with ant colony optimization,\u201d Fuzzy sets and systems, vol.149, no.1, pp.5-20, 2005. 10.1016\/j.fss.2004.07.014","DOI":"10.1016\/j.fss.2004.07.014"},{"key":"27","unstructured":"[27] B.A. Tama, \u201cLearning to prevent inactive student of Indonesia open university,\u201d Journal of Information Processing Systems, vol.11, no.2, pp.165-172, 2015. 10.3745\/jips.04.0015"},{"key":"28","doi-asserted-by":"publisher","unstructured":"[28] T.G. Dietterich, \u201cApproximate statistical tests for comparing supervised classification learning algorithms,\u201d Neural computation, vol.10, no.7, pp.1895-1923, 1998. 10.1162\/089976698300017197","DOI":"10.1162\/089976698300017197"},{"key":"29","doi-asserted-by":"publisher","unstructured":"[29] K. Hornik, C. Buchta, and A. Zeileis, \u201cOpen-source machine learning: R meets weka,\u201d Computational Statistics, vol.24, no.2, pp.225-232, 2009. 10.1007\/s00180-008-0119-7","DOI":"10.1007\/s00180-008-0119-7"},{"key":"30","doi-asserted-by":"publisher","unstructured":"[30] S. Garc\u00eda, A. Fern\u00e1ndez, J. Luengo, and F. Herrera, \u201cAdvanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power,\u201d Information Sciences, vol.180, no.10, pp.2044-2064, 2010. 10.1016\/j.ins.2009.12.010","DOI":"10.1016\/j.ins.2009.12.010"},{"key":"31","unstructured":"[31] J. Dem\u0160ar, \u201cStatistical comparisons of classifiers over multiple data sets,\u201d Journal of Machine learning research, vol.7, no.Jan, pp.1-30, 2006."},{"key":"32","unstructured":"[32] E. Ozcan and C.K. Mohan, \u201cParticle swarm optimization: surfing the waves,\u201d Proc. 1999 Congress on Evolutionary Computation, 1999, CEC 99, IEEE, 1999. 10.1109\/cec.1999.785510"},{"key":"33","doi-asserted-by":"publisher","unstructured":"[33] R.K. Sivagaminathan and S. Ramakrishnan, \u201cA hybrid approach for feature subset selection using neural networks and ant colony optimization,\u201d Expert. Syst. Appl., vol.33, no.1, pp.49-60, 2007. 10.1016\/j.eswa.2006.04.010","DOI":"10.1016\/j.eswa.2006.04.010"},{"key":"34","doi-asserted-by":"crossref","unstructured":"[34] N. Japkowicz and M. Shah, Evaluating learning algorithms: A classification perspective, Cambridge University Press, 2011. 10.1017\/cbo9780511921803","DOI":"10.1017\/CBO9780511921803"},{"key":"35","doi-asserted-by":"crossref","unstructured":"[35] M. Panda, A. Abraham, and M.R. Patra, \u201cDiscriminative multinomial naive bayes for network intrusion detection,\u201d 2010 Sixth International Conference on Information Assurance and Security (IAS), pp.5-10, IEEE, 2010. 10.1109\/isias.2010.5604193","DOI":"10.1109\/ISIAS.2010.5604193"},{"key":"36","unstructured":"[36] H.M. Harb and A.S. Desuky, \u201cAdaboost ensemble with genetic algorithm post optimization for intrusion detection,\u201d International Journal of Computer Science Issues, vol.8, no.5, 1, 2011."}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E100.D\/8\/E100.D_2016ICP0018\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T19:17:52Z","timestamp":1750792672000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E100.D\/8\/E100.D_2016ICP0018\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":36,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2017]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2016icp0018","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]}}}