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national security vulnerability database classification based on an lda topic model
Liao Xiaofeng ; Wang Yongji ; Fan Xiubin ; Wu Jingzheng
刊名Qinghua Daxue Xuebao/Journal of Tsinghua University
2012
卷号52期号:10页码:1351-1355
关键词漏洞分类 隐含Dirichlet分布(LDA) 支持向量机(SVM) 中国国家信息安全漏洞库(CNNVD)
ISSN号1000-0054
中文摘要采用隐含Dirichlet分布主题模型(latent Dirichletallocation,LDA)和支持向量机(support vector machine,SVM)相结合的方法,在主题向量空间构建一个自动漏洞分类器。以中国国家信息安全漏洞库(CNNVD)中漏洞记录为实验数据。实验表明:基于主题向量构建的分类器的分类准确度比直接使用词汇向量构建的分类器有8%的提高。
英文摘要The current vulnerabilities in China are analyzed using a dataset from the China National Vulnerability Database of Information Security (CNNVD), with a combined latent Dirichlet allocation (LDA) topic model and a support vector machine (SVM) to construct a classifier in the topic vector space. Tests show that the classifier based on topic vectors has about 8% better classification performance than that based on text vectors.
收录类别EI ; CNKI
资助信息国家重点科技专题“核高基”资助项目(2010ZX01036-001-002)
语种中文
公开日期2013-09-17
内容类型期刊论文
源URL[http://ir.iscas.ac.cn/handle/311060/15141]  
专题软件研究所_软件所图书馆_期刊论文
推荐引用方式
GB/T 7714
Liao Xiaofeng,Wang Yongji,Fan Xiubin,et al. national security vulnerability database classification based on an lda topic model[J]. Qinghua Daxue Xuebao/Journal of Tsinghua University,2012,52(10):1351-1355.
APA Liao Xiaofeng,Wang Yongji,Fan Xiubin,&Wu Jingzheng.(2012).national security vulnerability database classification based on an lda topic model.Qinghua Daxue Xuebao/Journal of Tsinghua University,52(10),1351-1355.
MLA Liao Xiaofeng,et al."national security vulnerability database classification based on an lda topic model".Qinghua Daxue Xuebao/Journal of Tsinghua University 52.10(2012):1351-1355.
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