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摘要:Network attacks corrupt or destroy the information and services and it affect the integrity and confidentiality of network system. It can be classified as Denial of Service Attack (DoS), User to Root Attack (U2R), Remote to Local Attack (R2L) and Probing attack. In network security, a lot of researchers attract towards intrusion attacks and normal network traffic classification problem as it is a very challenging and critical problem. This paper presents an Artificial Immune System based approach for anomaly based network intrusion detection system. Artificial Immune System (AIS) algorithm is Meta-heuristic method which is used for clustering and pattern recognition. In addition, this article explains that the Clonal Selection Classification Algorithm (CSCA) can be applied to anomaly based network intrusion detection system and it can attain better solution only with very less number of antibodies. This model is compared with other approaches like Na ve Bayes, Random Tree and Support Vector Machine (SVM) that have been used previously to solve the same problem.
会议名称:

The 3rd International Conference on Intelligent Computational Systems(ICICS’2013);The 3rd International Conference on Mechanical,Automotive and Materials Engineering(ICMAME’2013);The 3rd International Conference on Electronics,Biomedical Engineering and its Applications(ICEBEA’2013);The 3rd International Conference on Ecological,Environmental and Biological Sciences(ICEEBS’2013);The 3rd International Conference on Business,Economics,Management and BehavioralSciences 2013(ICBEMBS’2013);The 3rd International Conference on Applied Mathematics and Pharmaceutical Sciences(ICAMPS’2013)

会议时间:

2013-04-29;2013-04-29;2013-04-29;2013-04-29;2013-04-29;2013-04-29

会议地点:

Singapore;Singapore;Singapore;Singapore;Singapore;Singapore

  • 专辑:

    信息科技

  • 专题:

    互联网技术

  • 分类号:

    TP393.08

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