Intrusion detection based on rough set and artificial immune

被引:0
|
作者
张玲 [1 ]
Sun Haiyan [1 ]
Cui Jiantao [1 ]
Yang Hua [1 ]
Huang Yan [1 ]
机构
[1] Software Engineering College,Zhengzhou University of Light Industry
基金
中国国家自然科学基金;
关键词
rough set; artificial immune; anomaly intrusion detection; rough set and artificial immune(RSAI-IDA);
D O I
暂无
中图分类号
TP18 [人工智能理论]; TP393.08 [];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ; 0839 ; 1402 ;
摘要
In order to increase intrusion detection rate and decrease false positive detection rate,a novel intrusion detection algorithm based on rough set and artificial immune( RSAI-IDA) is proposed.Using artificial immune in intrusion detection,anomaly actions are detected adaptively,and with rough set,effective antibodies can be obtained. A scheme,in which antibodies are partly generated randomly and others are from the artificial immune algorithm,is applied to ensure the antibodies diversity. Finally,simulations of RSAI-IDA and comparisons with other algorithms are given. The experimental results illustrate that the novel algorithm achieves more effective performances on anomaly intrusion detection,where the algorithm’s time complexity decreases,the true positive detection rate increases,and the false positive detection rate is decreased.
引用
收藏
页码:368 / 375
页数:8
相关论文
共 50 条
  • [1] Research on Intrusion Detection of Database based on Rough Set
    Zhang, Jihong
    Chen, Xiaoquan
    INTERNATIONAL CONFERENCE ON SOLID STATE DEVICES AND MATERIALS SCIENCE, 2012, 25 : 1637 - 1641
  • [2] An intrusion detection method based on rough set and SVM algorithm
    Hong, P
    Zhang, DN
    Wu, TF
    2004 INTERNATIONAL CONFERENCE ON COMMUNICATION, CIRCUITS, AND SYSTEMS, VOLS 1 AND 2: VOL 1: COMMUNICATION THEORY AND SYSTEMS, 2004, : 1127 - 1130
  • [3] Research on Intrusion Detection Based on Genetic Algorithm and Rough Set
    Li, Shiyong
    Zhu, Yanli
    Ma, Lijuan
    Liang, Yunjuan
    2011 INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND NEURAL COMPUTING (FSNC 2011), VOL I, 2011, : 175 - 177
  • [4] ANOMALY INTRUSION DETECTION METHOD BASED ON ROUGH SET THEORY
    Li, Yong-Zhong
    Zhao, Bo
    Xu, Jing
    Yang, Ge
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION, VOLS 1 AND 2, 2008, : 764 - 770
  • [5] Intrusion Detection Model Based on Rough Set and Random Forest
    Ling, Zhang
    Wei, Zhang Jian
    Mei, Fan Nai
    Hao, Zhao Hao
    INTERNATIONAL JOURNAL OF GRID AND HIGH PERFORMANCE COMPUTING, 2022, 14 (01)
  • [6] A new framework for intrusion detection based on rough set theory
    Li, ZJ
    Wu, Y
    Wang, GY
    Hai, YJ
    He, YP
    DATA MINING AND KNOWLEDGE DISCOVERY: THEORY, TOOLS, AND TECHNOLOGY VI, 2004, 5433 : 122 - 130
  • [7] Intrusion detection using rough set classification
    Zhang L.-H.
    Zhang G.-H.
    Yu L.
    Zhang J.
    Bai Y.-C.
    Journal of Zhejiang University-SCIENCE A, 2004, 5 (9): : 1076 - 1086
  • [8] Intrusion detection using rough set classification
    张连华
    张冠华
    郁郎
    张洁
    白英彩
    Journal of Zhejiang University Science, 2004, (09) : 70 - 80
  • [9] Integrated intrusion detection model based on artificial immune
    ZHANG Ling
    BAI Zhong-ying
    LU Yun-long
    ZHA Ya-xing
    LI Zhen-wen
    The Journal of China Universities of Posts and Telecommunications, 2014, 21 (02) : 83 - 90
  • [10] Integrated intrusion detection model based on artificial immune
    Zhang, Ling
    Bai, Zhong-Ying
    Lu, Yun-Long
    Zha, Ya-Xing
    Li, Zhen-Wen
    Journal of China Universities of Posts and Telecommunications, 2014, 21 (02): : 83 - 90