Analyzing CVE Database Using Unsupervised Topic Modelling

V. Mounika, Xiaohong Yuan, Kanishka Bandaru
{"title":"Analyzing CVE Database Using Unsupervised Topic Modelling","authors":"V. Mounika, Xiaohong Yuan, Kanishka Bandaru","doi":"10.1109/CSCI49370.2019.00019","DOIUrl":null,"url":null,"abstract":"This paper describes our study of the vulnerability reports in the Common Vulnerability and Exposures (CVE) database by using topic modeling on the description texts of the vulnerabilities. Prevalent vulnerability types were found, and new trends of vulnerabilities were discovered by studying the 121,716 unique CVE entries that are reported from January 1999 to July 2019. The topics found through topic modeling were mapped to OWASP Top 10 vulnerabilities. It was found that the OWASP vulnerabilities A2: 2017-Broken Authentication, A4:2017-XML External Entities (XXE), and A5:2017-Broken Access Control increased, yet the vulnerability A7:2017-Cross-Site Scripting (XSS) had a steep decrease over the period of 20 years.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCI49370.2019.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

Abstract

This paper describes our study of the vulnerability reports in the Common Vulnerability and Exposures (CVE) database by using topic modeling on the description texts of the vulnerabilities. Prevalent vulnerability types were found, and new trends of vulnerabilities were discovered by studying the 121,716 unique CVE entries that are reported from January 1999 to July 2019. The topics found through topic modeling were mapped to OWASP Top 10 vulnerabilities. It was found that the OWASP vulnerabilities A2: 2017-Broken Authentication, A4:2017-XML External Entities (XXE), and A5:2017-Broken Access Control increased, yet the vulnerability A7:2017-Cross-Site Scripting (XSS) had a steep decrease over the period of 20 years.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用无监督主题建模分析CVE数据库
本文采用对漏洞描述文本进行主题建模的方法,对CVE数据库中的漏洞报告进行了研究。通过对1999年1月至2019年7月报告的121,716个独特CVE条目进行研究,发现了常见的漏洞类型,并发现了漏洞的新趋势。通过主题建模发现的主题映射到OWASP Top 10漏洞。结果发现,OWASP漏洞A2: 2017-Broken Authentication、A4:2017-XML External Entities (XXE)和A5:2017-Broken Access Control增加了,而漏洞A7:2017-Cross-Site Scripting (XSS)在过去20年里急剧减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Temperature Prediction Based on Long Short Term Memory Networks Extending a Soft-Core RISC-V Processor to Accelerate CNN Inference Uncovering Los Angeles Tourists' Patterns Using Geospatial Analysis and Supervised Machine Learning with Random Forest Predictors A Framework for Leveraging Business Intelligence to Manage Transactional Data Flows between Private Healthcare Providers and Medical Aid Administrators Feasibility Study of a Consumer Multi-Sensory Wristband to Monitor Sleep Disorder
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1