VSkLCG A Method for Cross-Platform Vulnerability Search in Firmware

Mushuai Han, Dongdong Zhao, Hong Lin, D. Zhou, Jianwen Xiang, Zhongjin Liu, Yanzhen Xing
{"title":"VSkLCG A Method for Cross-Platform Vulnerability Search in Firmware","authors":"Mushuai Han, Dongdong Zhao, Hong Lin, D. Zhou, Jianwen Xiang, Zhongjin Liu, Yanzhen Xing","doi":"10.1109/DSA.2019.00061","DOIUrl":null,"url":null,"abstract":"Vulnerabilities in firmware will make a system at risk. Because of code reuse, the same vulnerability may occur on different platforms. Therefore, searching vulnerabilities across different platforms is of great significance. Due to the difficulty in obtaining the source code of firmware, there is a need to search vulnerabilities at the binary level. However, the prior methods mainly work at the same platform, which can't be directly extended to the case of cross-platform. In this paper, we propose a multistage method to search cross-platform vulnerabilities in firmware. Given a vulnerable function in a platform, our objective is to find its homologous vulnerability in another platform. To ensure the efficiency, we identify a set of robust numeric features and use the k-Nearest Neighbors (kNN) algorithm to obtain possible vulnerable functions. To improve the accuracy, we adopt the bipartite matching algorithm to calculate the distance between functions based on the local call graphs (LCGs) of functions and the call frequency between functions. We have implemented a prototype of our approach, called VSkLCG, which supports three platforms (ARM, MIPS, x86). The experimental results show that our method can search some vulnerabilities in firmware with a high accuracy while maintaining efficiency.","PeriodicalId":342719,"journal":{"name":"2019 6th International Conference on Dependable Systems and Their Applications (DSA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 6th International Conference on Dependable Systems and Their Applications (DSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSA.2019.00061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Vulnerabilities in firmware will make a system at risk. Because of code reuse, the same vulnerability may occur on different platforms. Therefore, searching vulnerabilities across different platforms is of great significance. Due to the difficulty in obtaining the source code of firmware, there is a need to search vulnerabilities at the binary level. However, the prior methods mainly work at the same platform, which can't be directly extended to the case of cross-platform. In this paper, we propose a multistage method to search cross-platform vulnerabilities in firmware. Given a vulnerable function in a platform, our objective is to find its homologous vulnerability in another platform. To ensure the efficiency, we identify a set of robust numeric features and use the k-Nearest Neighbors (kNN) algorithm to obtain possible vulnerable functions. To improve the accuracy, we adopt the bipartite matching algorithm to calculate the distance between functions based on the local call graphs (LCGs) of functions and the call frequency between functions. We have implemented a prototype of our approach, called VSkLCG, which supports three platforms (ARM, MIPS, x86). The experimental results show that our method can search some vulnerabilities in firmware with a high accuracy while maintaining efficiency.
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
基于VSkLCG的固件跨平台漏洞搜索方法
固件中的漏洞将使系统处于危险之中。由于代码重用,相同的漏洞可能出现在不同的平台上。因此,跨平台搜索漏洞具有重要意义。由于固件源代码难以获取,因此需要在二进制级别搜索漏洞。然而,之前的方法主要是在同一平台上工作,不能直接扩展到跨平台的情况。在本文中,我们提出了一种多级搜索固件跨平台漏洞的方法。给定一个脆弱的函数在一个平台,我们的目标是发现其同源漏洞在另一个平台。为了保证效率,我们识别了一组鲁棒的数字特征,并使用k-最近邻(kNN)算法来获取可能的脆弱函数。为了提高准确率,我们采用基于函数局部调用图和函数之间调用频率的二部匹配算法来计算函数之间的距离。我们已经实现了我们的方法的原型,称为VSkLCG,它支持三个平台(ARM, MIPS, x86)。实验结果表明,该方法可以在保持效率的前提下,以较高的精度搜索固件中的某些漏洞。
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
Rational Design of the Appearance of Complex Industrial Products Based on Visual Communication Research on Anti-Noise Performance of New Chaos Criterion Research on Railway Intelligent Operation and Maintenance and Its System Architecture Research on Industrial Software Testing Knowledge Database Based on Ontology Research on Design and Verification of Sobel Image Edge Detection Based on High Level Synthesis
×
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