journal6 ›› 2013, Vol. 34 ›› Issue (4): 62-66.DOI: 10.3969/j.issn.1007-2985.2013.03.014

• Information and communication • Previous Articles     Next Articles

Construction of a SVM Learning Model in the Categorization Framework for CVE


  1.   (College of Information Science and Engineering,Jishou University,Jishou,416000,Hunan China)
  • Online:2013-07-25 Published:2013-07-18

Abstract: In the categorization framework for CVE,this paper designs and constructs a learning model based on SVM,so that it can categorize the CVE according to the different taxonomic features.In the process of constructing a learning model based on SVM,first of all,the training data is generated according to the different taxonomic features in the several vulnerability databases,then a data fusion and cleansing process are designed to eliminate the inconsistencies of data,and finally the n-fold cross-validation method is used to evaluate the effect of the model.The learning model has been verified to have better performance of CVE classification.

Key words: support vector machine (SVM), common vulnerabilities and exposures (CVE), taxonomic feature,classification accuracy

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