ISCAS OpenIR
black-box testing based on colorful taint analysis
Chen Kai; Feng DengGuo; Su PuRui; Zhang YingJun
2012
SourceSCIENCE CHINA-INFORMATION SCIENCES
ISSN1674-733X
Volume55Issue:1Pages:171-183
English AbstractSoftware vulnerability detection is one of the most important methods for guaranteeing software security. Two main classes of methods can detect vulnerabilities in binary files: white-box testing and black-box testing. The former needs to construct and solve path constraints to detect vulnerabilities. It has two main drawbacks: path exploding and complexity of constraints. The latter often aimlessly exhausts various inputs to test binary files. This paper combines both testing methods to detect vulnerabilities in binary files. By analyzing the input elements that affect check condition corresponding to a certain check point, we can generate one class of inputs that get to the check point to increase fuzzing efficiency. By analyzing the relationship between guard conditions and check condition, the redundant check points are removed. Colorful taint analysis method (CTAM) is proposed to compute guard conditions, which is more efficient than traditional taint analysis method (TTAM). We implemented a prototype and made several experiments on it. The results showed that our method could increase the efficiency of black-box testing.; Software vulnerability detection is one of the most important methods for guaranteeing software security. Two main classes of methods can detect vulnerabilities in binary files: white-box testing and black-box testing. The former needs to construct and solve path constraints to detect vulnerabilities. It has two main drawbacks: path exploding and complexity of constraints. The latter often aimlessly exhausts various inputs to test binary files. This paper combines both testing methods to detect vulnerabilities in binary files. By analyzing the input elements that affect check condition corresponding to a certain check point, we can generate one class of inputs that get to the check point to increase fuzzing efficiency. By analyzing the relationship between guard conditions and check condition, the redundant check points are removed. Colorful taint analysis method (CTAM) is proposed to compute guard conditions, which is more efficient than traditional taint analysis method (TTAM). We implemented a prototype and made several experiments on it. The results showed that our method could increase the efficiency of black-box testing.
Indexed TypeSCI
KeywordSoftware Testing Vulnerability Detection Dynamic Testing Black-box Testing Colorful Taint Analysis
DepartmentChen Kai; Feng DengGuo; Su PuRui; Zhang YingJun Chinese Acad Sci State Key Lab Informat Secur Inst Software Beijing 100190 Peoples R China. Chen Kai; Zhang YingJun Chinese Acad Sci State Key Lab Informat Secur Grad Univ Beijing 100049 Peoples R China. Chen Kai; Zhang YingJun Natl Engn Res Ctr Informat Secur Beijing 100190 Peoples R China.
SubjectComputer Science
SponsorshipNational Natural Science Foundation of China 60970028, 60703076, 61073179
Language英语
WOS IDWOS:000298651900020
Citation statistics
Content Type期刊论文
URIhttp://ir.iscas.ac.cn/handle/311060/15095
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Chen Kai,Feng DengGuo,Su PuRui,et al. black-box testing based on colorful taint analysis[J]. SCIENCE CHINA-INFORMATION SCIENCES,2012,55(1):171-183.
APA Chen Kai,Feng DengGuo,Su PuRui,&Zhang YingJun.(2012).black-box testing based on colorful taint analysis.SCIENCE CHINA-INFORMATION SCIENCES,55(1),171-183.
MLA Chen Kai,et al."black-box testing based on colorful taint analysis".SCIENCE CHINA-INFORMATION SCIENCES 55.1(2012):171-183.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Chen Kai]'s Articles
[Feng DengGuo]'s Articles
[Su PuRui]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chen Kai]'s Articles
[Feng DengGuo]'s Articles
[Su PuRui]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chen Kai]'s Articles
[Feng DengGuo]'s Articles
[Su PuRui]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.