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基于K-最近邻算法的未知病毒检测 被引量:15

Unknown Computer Virus Detection Based on K-Nearest Neighbor Algorithm
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摘要 因为准确检测计算机病毒是不可判定的,故该文提出了一种基于实例学习的k-最近邻算法来实现对计算机病毒的近似检测。该法可以克服病毒特征代码扫描法不能识别未知病毒的缺点。在该检测方法的基础上,文章设计了一个病毒检测网络模型,此模型适用于实时在线系统中的病毒检测,既可以实现对已知病毒的查杀,又可以对可疑程序行为进行分析评判,最终实现对未知病毒的识别。 Because precise determination of a virus by its appearance is undecidable,a K-nearest neighbor Algorithm based on sample learning to detect computer virus approximately is presented in this paper.It can overcome the short-age of normal virus scanner-which can not detect unknown virus.Based on this method,a virus detect network model is designed also.This model fits to detect viurs in the on-line system,it alse detect known and unknown computer virus by analyzing the program's behavior.
出处 《计算机工程与应用》 CSCD 北大核心 2005年第6期7-10,共4页 Computer Engineering and Applications
基金 国家自然科学基金项目(编号:60373023)资助
关键词 计算机病毒 K-最近邻算法 病毒检测 computer virus,K-Nearest Neighbor Algorithm(KNN),virus detection
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参考文献5

  • 1F Cohen. Computer Viruses:Theory and Experiments[J].Computers & Security, 1987; 6 ( 1 ): 22~35.
  • 2Diomidis Spinellis. Reliable Identification of Bounded-LengthViruses Is NP-Complete [J].IEEE TRANSACTIONS ON INFORMATIONTHEORY,2003 ;49( 1 ) :280~284.
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  • 5David J Kruglinski,Scot Wingo,George Shepherd..Programming Visual C++[M].Washington: Micosoft Press, 1998.

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