Reference : An Integrated Approach for Effective Injection Vulnerability Analysis of Web Applicat... |
Scientific journals : Article | |||
Engineering, computing & technology : Computer science | |||
Security, Reliability and Trust | |||
http://hdl.handle.net/10993/32059 | |||
An Integrated Approach for Effective Injection Vulnerability Analysis of Web Applications through Security Slicing and Hybrid Constraint Solving | |
English | |
Thome, Julian [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >] | |
Shar, Lwin Khin [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >] | |
Bianculli, Domenico ![]() | |
Briand, Lionel ![]() | |
Feb-2020 | |
IEEE Transactions on Software Engineering | |
Institute of Electrical and Electronics Engineers | |
46 | |
2 | |
163--195 | |
Yes (verified by ORBilu) | |
International | |
0098-5589 | |
New York | |
NY | |
[en] Vulnerability detection ; Constraint solving ; Static analysis ; Search-based software engineering | |
[en] 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. | |
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab) | |
Fonds National de la Recherche - FnR | |
Researchers ; Professionals ; Students | |
http://hdl.handle.net/10993/32059 | |
10.1109/TSE.2018.2844343 | |
FnR ; FNR9132112 > Julian Thomé > HyVAn > A Scalable And Accurate Hybrid Vulnerability Analysis Framework > 01/09/2014 > 14/04/2018 > 2014 |
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