Recommending Attack Patterns for Software Requirements Document

Mounika Vanamala, Jairen Gilmore, Xiaohong Yuan, K. Roy
{"title":"Recommending Attack Patterns for Software Requirements Document","authors":"Mounika Vanamala, Jairen Gilmore, Xiaohong Yuan, K. Roy","doi":"10.1109/CSCI51800.2020.00334","DOIUrl":null,"url":null,"abstract":"To develop secure software, software developers need to know the potential threats to the software. Knowledge captured in the Common Attack Pattern Enumeration and Classification (CAPEC) database can help software developers to understand how attackers target application weaknesses. In this paper, we present a method of recommending CAPEC attack patterns based on software requirement specification (SRS) documents. The method uses topic modelling to extract topics from each attack pattern and to extract topics from the software system description, user classes, use cases, and function requirements within the SRS documents. Attack patterns are recommended by calculating the distance measure of each attack pattern topic distribution and each SRS topic distribution using cosine similarity. Attack patterns are then ranked from maximum to minimum. The top attack patterns are then recommended to the software developers as the most relevant to the software system under development.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCI51800.2020.00334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

To develop secure software, software developers need to know the potential threats to the software. Knowledge captured in the Common Attack Pattern Enumeration and Classification (CAPEC) database can help software developers to understand how attackers target application weaknesses. In this paper, we present a method of recommending CAPEC attack patterns based on software requirement specification (SRS) documents. The method uses topic modelling to extract topics from each attack pattern and to extract topics from the software system description, user classes, use cases, and function requirements within the SRS documents. Attack patterns are recommended by calculating the distance measure of each attack pattern topic distribution and each SRS topic distribution using cosine similarity. Attack patterns are then ranked from maximum to minimum. The top attack patterns are then recommended to the software developers as the most relevant to the software system under development.
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
为软件需求文档推荐攻击模式
为了开发安全的软件,软件开发人员需要了解软件的潜在威胁。在通用攻击模式枚举和分类(CAPEC)数据库中获取的知识可以帮助软件开发人员了解攻击者如何针对应用程序弱点进行攻击。本文提出了一种基于软件需求规范(SRS)文档的CAPEC攻击模式推荐方法。该方法使用主题建模从每个攻击模式中提取主题,并从SRS文档中的软件系统描述、用户类、用例和功能需求中提取主题。利用余弦相似度计算每个攻击模式主题分布和每个SRS主题分布的距离度量,从而推荐攻击模式。然后将攻击模式从最大到最小排序。然后将顶级攻击模式作为与正在开发的软件系统最相关的模式推荐给软件开发人员。
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
First Success of Cancer Gene Data Analysis of 169 Microarrays for Medical Diagnosis Artificial Intelligence in Computerized Adaptive Testing Evidence for Monitoring the User and Computing the User’s trust Transfer of Hierarchical Reinforcement Learning Structures for Robotic Manipulation Tasks An open-source application built with R programming language for clinical laboratories to innovate process of excellence and overcome the uncertain outlook during the global healthcare crisis
×
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