A memory-related vulnerability detection approach based on vulnerability model with Petri Net
With the continuous development of information technology, software vulnerabilities have become a critical threat to information security. Post-release detection of memory leaks, double free and use after free is one of the most challenging research problems in software vulnerability analysis. To ta...
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Published in | Journal of logical and algebraic methods in programming Vol. 132; p. 100859 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Inc
01.04.2023
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Subjects | |
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Abstract | With the continuous development of information technology, software vulnerabilities have become a critical threat to information security. Post-release detection of memory leaks, double free and use after free is one of the most challenging research problems in software vulnerability analysis. To tackle this challenge, we introduce a vulnerability model based on Petri Net. We consider the characteristics and causes of vulnerabilities, modeling is conducted from the subject and environment of vulnerabilities. Based on this vulnerability model, we propose a memory-related vulnerability detection framework based on vulnerability model (MRVD-VM) and its vulnerability detection algorithm based on vulnerability mode (VDA-VM). The results of experiments on Juliet Test Suite 1.2 for C_CPP show that MRVD-VM significantly outperforms three state-of-the-art baseline tools, including Cppcheck, Flawfinder, and Splint, in detecting memory leaks, double free and use after free.
•We propose a vulnerability model based on Petri Net.•We propose a vulnerability detection framework based on the proposed vulnerability model.•Compared with three detection tools, our approach is better. |
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AbstractList | With the continuous development of information technology, software vulnerabilities have become a critical threat to information security. Post-release detection of memory leaks, double free and use after free is one of the most challenging research problems in software vulnerability analysis. To tackle this challenge, we introduce a vulnerability model based on Petri Net. We consider the characteristics and causes of vulnerabilities, modeling is conducted from the subject and environment of vulnerabilities. Based on this vulnerability model, we propose a memory-related vulnerability detection framework based on vulnerability model (MRVD-VM) and its vulnerability detection algorithm based on vulnerability mode (VDA-VM). The results of experiments on Juliet Test Suite 1.2 for C_CPP show that MRVD-VM significantly outperforms three state-of-the-art baseline tools, including Cppcheck, Flawfinder, and Splint, in detecting memory leaks, double free and use after free.
•We propose a vulnerability model based on Petri Net.•We propose a vulnerability detection framework based on the proposed vulnerability model.•Compared with three detection tools, our approach is better. |
ArticleNumber | 100859 |
Author | Ma, Liang Zhang, Chi Zhang, Lin Cai, Saihua Chen, Jinfu |
Author_xml | – sequence: 1 givenname: Jinfu surname: Chen fullname: Chen, Jinfu organization: School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China – sequence: 2 givenname: Chi surname: Zhang fullname: Zhang, Chi organization: School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China – sequence: 3 givenname: Saihua orcidid: 0000-0003-0743-1156 surname: Cai fullname: Cai, Saihua email: caisaih@ujs.edu.cn organization: School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China – sequence: 4 givenname: Lin surname: Zhang fullname: Zhang, Lin organization: School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China – sequence: 5 givenname: Liang surname: Ma fullname: Ma, Liang organization: School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China |
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Cites_doi | 10.1145/3436877 10.1016/j.cose.2022.102639 10.1109/TSE.2018.2869336 10.1109/TDSC.2017.2753803 10.26599/TST.2019.9010068 10.1002/spe.2870 10.1002/smr.2164 10.1016/j.jss.2020.110616 10.1007/s10796-020-10004-9 10.1007/s11390-021-1600-9 |
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Keywords | Vulnerability model Use after free Double free Memory leak Vulnerability detection |
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