期刊文献+

基于支持向量机和Hurst指数的集成入侵检测研究 被引量:1

The Research of Integrated Intrusion Detection Based on SVM and Hurst Parameter
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摘要 提出了一种将SVM算法与Hurst指数相结合的入侵检测方法—集成入侵检测。DARPA上的测试结果表明,该方法不仅能够发现网络中已知的攻击,还能够确定网络中未知的攻击,提高了入侵检测的效率。 A new integrated intrusion detection approach is presented based on support vector machine (SVM) and Hurst parameter. The testing results on the DARPA data show that the combined method can detect the possible presence of not only known attacks, but also unknown attacks, and improve detection rate.
出处 《微计算机信息》 北大核心 2006年第03X期51-52,64,共3页 Control & Automation
基金 国家自然科学基金 项目编号(60372019)
关键词 集成入侵检测 支持向量机 HURST参数 Integrated Intrusion Detection Support vector machine Hurst parameter
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参考文献3

  • 1DARPA 199g data set[DB/OL]. http://www.ll.mit.edu/IST/ideval/data/1998/1998_data index, html,1998.
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二级参考文献6

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共引文献9

同被引文献5

  • 1AXELSSON S.Research in intrusion detection system:a survey[R].Chalmers University of Technology,CMU/SEI Technical Report (CMU/SEI-99-TR-028),1999.
  • 2HAI JIN,JIANHUA SUN,HAO CHEN,et al.A fuzzy data mining based intrusion detection model:proc of 10th Int Workshop on Future Trends of Distributed Computing Systems[R].Suzhou,China,2004:191-197.
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