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Detection technology for unknown virus based on data farming

机译:基于数据耕作的未知病毒检测技术

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In order to improve the detection rate of unknown virus, this paper presented a detection technology for unknown computer virus based on data farming, which synthetically considered the types of viruses, feature extraction methods for viruses of different types, data classification algorithms and other factors. Firstly, this technology extracted the behavior feature of the files to be executed, and then analyzed the extracted feature data by means of improved data farming technology which absorbed naive bayes classification algorithm to detect whether the file to be executed contained viruses. Experimental results showed that this technology had the higher accuracy and lower error rate in unknown computer viruses detection.
机译:为了提高未知病毒的检测率,提出了一种基于数据耕种的未知计算机病毒检测技术,综合考虑了病毒的种类,不同类型病毒的特征提取方法,数据分类算法等因素。该技术首先提取待执行文件的行为特征,然后利用改进的数据耕种技术对提取的特征数据进行分析,该技术利用朴素贝叶斯分类算法来检测待执行文件是否包含病毒。实验结果表明,该技术在未知计算机病毒检测中具有较高的准确性和较低的错误率。

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