基于分类的未知病毒检测方法研究  

Research of Unknown Virus Detection Based on Classification Method

作　　者：熊俊[1] 

机构地区：[1]湖南警察学院,长沙410138

出　　处：《电脑开发与应用》2012年第11期20-23,共4页Computer Development & Applications

摘　　要：针对PE文件的静态信息,通过对未知病毒进行聚类分类分析,采用优化的初始聚类K-means算法,最终实现对病毒文件的相似度检测,无需运行PE文件即可判断其是否为病毒。该方法不仅克服了病毒特征码扫描无法识别未知病毒的缺点,而且相对于API序列检测方法免去了对文件进行脱壳等复杂操作,显著提高了检测速度。实验结果表明分类检测方法具有较好的准确性,有一定的应用价值。With PE file information as static characteristic, a classification method to detect unknown virus is proposed in this paper. In this paper, the K-means clustering algorithm based on the optimized initial cluster centers detects the similarity of the virus file ~ Without running the PE file, the classifier can determine whether it is virus or not. The method can overcome the shortage of virus feature scanning technology, which could not recognize unknown virus, and do not need for file shelling and other complex operations relative to the API sequence test methods, significantly improve the detection speed. Experiment results show that the detection method has better classification accuracy, so there is a certain practical value.

关 键 词：信息安全 PE文件静态信息 未知病毒检测 

分 类 号：TP309.5[自动化与计算机技术—计算机系统结构]