An integrated approach for effective injection vulnerability analysis of web applications through security slicing and hybrid constraint solving
Malicious users can attack Web applications by exploiting injection vulnerabilities in the source code. This work addresses the challenge of detecting injection vulnerabilities in the server-side code of Java Web applications in a scalable and effective way. We propose an integrated approach that se...
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sg-smu-ink.sis_research-58952020-02-13T08:19:24Z An integrated approach for effective injection vulnerability analysis of web applications through security slicing and hybrid constraint solving THOME, Julian SHAR, Lwin Khin BIANCULLI, Domenico BRIAND, Lionel Malicious users can attack Web applications by exploiting injection vulnerabilities in the source code. This work addresses the challenge of detecting injection vulnerabilities in the server-side code of Java Web applications in a scalable and effective way. We propose an integrated approach that seamlessly combines security slicing with hybrid constraint solving; the latter orchestrates automata-based solving with meta-heuristic search. We use static analysis to extract minimal program slices relevant to security from Web programs and to generate attack conditions. We then apply hybrid constraint solving to determine the satisfiability of attack conditions and thus detect vulnerabilities. The experimental results, using a benchmark comprising a set of diverse and representative Web applications/services as well as security benchmark applications, show that our approach (implemented in the JOACO tool) is significantly more effective at detecting injection vulnerabilities than state-of-the-art approaches, achieving 98% recall, without producing any false alarm. We also compared the constraint solving module of our approach with state-of-the-art constraint solvers, using six different benchmark suites; our approach correctly solved the highest number of constraints (665 out of 672), without producing any incorrect result, and was the one with the least number of time-out/failing cases. In both scenarios, the execution time was practically acceptable, given the offline nature of vulnerability detection. 2018-06-06T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4892 info:doi/10.1109/TSE.2018.2844343 https://ink.library.smu.edu.sg/context/sis_research/article/5895/viewcontent/an_integrated___AV.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Vulnerability detection constraint solving static analysis search-based software engineering Information Security Software Engineering |
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Vulnerability detection constraint solving static analysis search-based software engineering Information Security Software Engineering THOME, Julian SHAR, Lwin Khin BIANCULLI, Domenico BRIAND, Lionel An integrated approach for effective injection vulnerability analysis of web applications through security slicing and hybrid constraint solving |
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Malicious users can attack Web applications by exploiting injection vulnerabilities in the source code. This work addresses the challenge of detecting injection vulnerabilities in the server-side code of Java Web applications in a scalable and effective way. We propose an integrated approach that seamlessly combines security slicing with hybrid constraint solving; the latter orchestrates automata-based solving with meta-heuristic search. We use static analysis to extract minimal program slices relevant to security from Web programs and to generate attack conditions. We then apply hybrid constraint solving to determine the satisfiability of attack conditions and thus detect vulnerabilities. The experimental results, using a benchmark comprising a set of diverse and representative Web applications/services as well as security benchmark applications, show that our approach (implemented in the JOACO tool) is significantly more effective at detecting injection vulnerabilities than state-of-the-art approaches, achieving 98% recall, without producing any false alarm. We also compared the constraint solving module of our approach with state-of-the-art constraint solvers, using six different benchmark suites; our approach correctly solved the highest number of constraints (665 out of 672), without producing any incorrect result, and was the one with the least number of time-out/failing cases. In both scenarios, the execution time was practically acceptable, given the offline nature of vulnerability detection. |
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text |
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THOME, Julian SHAR, Lwin Khin BIANCULLI, Domenico BRIAND, Lionel |
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THOME, Julian SHAR, Lwin Khin BIANCULLI, Domenico BRIAND, Lionel |
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THOME, Julian |
title |
An integrated approach for effective injection vulnerability analysis of web applications through security slicing and hybrid constraint solving |
title_short |
An integrated approach for effective injection vulnerability analysis of web applications through security slicing and hybrid constraint solving |
title_full |
An integrated approach for effective injection vulnerability analysis of web applications through security slicing and hybrid constraint solving |
title_fullStr |
An integrated approach for effective injection vulnerability analysis of web applications through security slicing and hybrid constraint solving |
title_full_unstemmed |
An integrated approach for effective injection vulnerability analysis of web applications through security slicing and hybrid constraint solving |
title_sort |
integrated approach for effective injection vulnerability analysis of web applications through security slicing and hybrid constraint solving |
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Institutional Knowledge at Singapore Management University |
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2018 |
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https://ink.library.smu.edu.sg/sis_research/4892 https://ink.library.smu.edu.sg/context/sis_research/article/5895/viewcontent/an_integrated___AV.pdf |
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