基于改进隐马尔可夫模型的网络攻击检测方法
기우개진은마이가부모형적망락공격검측방법
Improved HMM model based method for detecting cyber attacks
  • 万方数据
    通信学报 통신학보
    JOURNAL OF CHINA INSTITUTE OF COMMUNICATIONS
    2010年 3期 95-101 ,共7页

    杨晓峰%孙明明%胡雪蕾%杨静宇

    양효봉%손명명%호설뢰%양정우

    网络安全%网络攻击%入侵检测%隐马尔可夫模型%语法推断 網絡安全%網絡攻擊%入侵檢測%隱馬爾可伕模型%語法推斷
    망락안전%망락공격%입침검측%은마이가부모형%어법추단
    network security%cyber attack%intrusion detection%HMM model%grammar inference
    提出了一种基于改进隐马尔可夫模型的网络攻击检测方法.正常的网络行为符合一定的语法规则,异常的行为会偏离正常的语法规则.通过对正常行为样本的学习得到的基于隐马尔可夫模型的语法可以根据网络行为和语法的符合程度有效地检测正常行为和攻击行为.在基于现实数据的实验测试中,得到了比较好的检测性能.
    제출료일충기우개진은마이가부모형적망락공격검측방법.정상적망락행위부합일정적어법규칙,이상적행위회편리정상적어법규칙.통과대정상행위양본적학습득도적기우은마이가부모형적어법가이근거망락행위화어법적부합정도유효지검측정상행위화공격행위.재기우현실수거적실험측시중,득도료비교호적검측성능.
    An improved HMM model based method for detecting cyber attacks was proposed. Normal network behaviors followed a regular grammar, while anomalies deviated the normal grammar. Grammar model represented by HMM model trained with normal network behavior samples easily distinguished normal and malicious requests by their contrasting conforming degrees. A significantly improved performance was achieved in real data tests compared with other anomaly methods.
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