Modeling intrusion detection system using hybrid intelligent systems

被引:210
|
作者
Peddabachigari, Sandhya
Abraham, Ajith [1 ]
Grosan, Crina
Thomas, Johnson
机构
[1] Chung Ang Univ, Sch Engn & Comp Sci, Seoul, South Korea
[2] Oklahoma State Univ, Dept Comp Sci, Stillwater, OK 74106 USA
[3] Univ Babes Bolyai, Dept Comp Sci, R-3400 Cluj Napoca, Romania
关键词
intrusion detection system; hybrid intelligent system; decision trees; support vector machines; ensemble approach;
D O I
10.1016/j.jnca.2005.06.003
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The process of monitoring the events occurring in a computer. system or network and analyzing them for sign of intrusions is known as intrusion detection system (IDS). This paper presents two hybrid approaches for modeling IDS. Decision trees (DT) and support vector machines (SVM) are combined as a hierarchical hybrid intelligent system model (DT-SVM) and an ensemble approach combining the base classifiers. The hybrid intrusion detection model combines the individual base classifiers and other hybrid machine learning paradigms to maximize detection accuracy and minimize computational complexity. Empirical results illustrate that the proposed hybrid systems provide more accurate intrusion detection systems. (C) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:114 / 132
页数:19
相关论文
共 50 条
  • [41] Intelligent Intrusion Detection System Model Using Rough Neural Network
    YAN Huai-zhi 1
    2.National Key Laboratory of Mechatronics Engineering and Control
    [J]. Wuhan University Journal of Natural Sciences, 2005, (01) : 119 - 122
  • [42] Intelligent Network Intrusion Detection System using Data Mining Techniques
    Sultana, Amreen
    Jabbar, M. A.
    [J]. PROCEEDINGS OF THE 2016 2ND INTERNATIONAL CONFERENCE ON APPLIED AND THEORETICAL COMPUTING AND COMMUNICATION TECHNOLOGY (ICATCCT), 2016, : 329 - 333
  • [43] Intelligent Intrusion Detection System Using Clustered Self Organized Map
    Almi'ani, Muder
    Abu Ghazleh, Alia
    Al-Rahayfeh, Amer
    Razaque, Abdul
    [J]. 2018 FIFTH INTERNATIONAL CONFERENCE ON SOFTWARE DEFINED SYSTEMS (SDS), 2018, : 138 - 144
  • [44] An intelligent intrusion detection system by using hierarchically structured learning automata
    Jamali, Shahram
    Jafarzadeh, Parisa
    [J]. NEURAL COMPUTING & APPLICATIONS, 2017, 28 (05): : 1001 - 1008
  • [45] An Intelligent Intrusion Detection System in Smart Grid Using PRNN Classifier
    Ganesan, P.
    Xavier, S. Arockia Edwin
    [J]. INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2023, 35 (03): : 2979 - 2996
  • [46] An intelligent intrusion detection system by using hierarchically structured learning automata
    Shahram Jamali
    Parisa Jafarzadeh
    [J]. Neural Computing and Applications, 2017, 28 : 1001 - 1008
  • [47] Hybrid Intrusion Detection in Information Systems
    Pierrot, David
    Harbi, Nouria
    Darmont, Jerome
    [J]. 2016 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND SECURITY (ICISS), 2014, : 27 - 31
  • [48] Hybrid Classifier Systems for Intrusion Detection
    Chou, Te-Shun
    Chou, Tsung-Nan
    [J]. 2009 7TH ANNUAL COMMUNICATION NETWORKS AND SERVICES RESEARCH CONFERENCE, 2009, : 286 - +
  • [49] Optimization of predictive performance of intrusion detection system using hybrid ensemble model for secure systems
    Abbas, Qaiser
    Hina, Sadaf
    Sajjad, Hamza
    Zaidi, Khurram Shabih
    Akbar, Rehan
    [J]. PEERJ COMPUTER SCIENCE, 2023, 9
  • [50] Intelligent query in intrusion detection audit system
    Gao, F
    Xue, Q
    Sun, JZ
    [J]. 2003 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-5, PROCEEDINGS, 2003, : 2212 - 2216