The Experts below are selected from a list of 77043 Experts worldwide ranked by ideXlab platform
Yang Liu - One of the best experts on this subject based on the ideXlab platform.
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atvhunter reliable Version Detection of third party libraries for vulnerability identification in android applications
International Conference on Software Engineering, 2021Co-Authors: Xian Zhan, Lingling Fan, Sen Chen, Tianming Liu, Xiapu Luo, Yang LiuAbstract:Third-party libraries (TPLs) as essential parts in the mobile ecosystem have become one of the most significant contributors to the huge success of Android, which facilitate the fast development of Android applications. Detecting TPLs in Android apps is also important for downstream tasks, such as malware and repackaged apps identification. To identify in-app TPLs, we need to solve several challenges, such as TPL dependency, code obfuscation, precise Version representation. Unfortunately, existing TPL Detection tools have been proved that they have not solved these challenges very well, let alone specify the exact TPL Versions. To this end, we propose a system, named ATVHunter, which can pinpoint the precise vulnerable in-app TPL Versions and provide detailed information about the vulnerabilities and TPLs. We propose a two-phase Detection approach to identify specific TPL Versions. Specifically, we extract the Control Flow Graphs as the coarse-grained feature to match potential TPLs in the pre-defined TPL database, and then extract opcode in each basic block of CFG as the fine-grained feature to identify the exact TPL Versions. We build a comprehensive TPL database (189,545 unique TPLs with 3,006,676 Versions) as the reference database. Meanwhile, to identify the vulnerable in-app TPL Versions, we also construct a comprehensive and known vulnerable TPL database containing 1,180 CVEs and 224 security bugs. Experimental results show AtVHunter outperforms state-of-the-art TPL Detection tools, achieving 90.55% precision and 88.79% recall with high efficiency, and is also resilient to widely-used obfuscation techniques and scalable for large-scale TPL Detection. Furthermore, to investigate the ecosystem of the vulnerable TPLs used by apps, we exploit newtool to conduct a large-scale analysis on 104,446 apps and find that 9,050 apps include vulnerable TPL Versions with 53,337 vulnerabilities and 7,480 security bugs, most of which are with high risks and are not recognized by app developers.
Xian Zhan - One of the best experts on this subject based on the ideXlab platform.
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atvhunter reliable Version Detection of third party libraries for vulnerability identification in android applications
International Conference on Software Engineering, 2021Co-Authors: Xian Zhan, Lingling Fan, Sen Chen, Tianming Liu, Xiapu Luo, Yang LiuAbstract:Third-party libraries (TPLs) as essential parts in the mobile ecosystem have become one of the most significant contributors to the huge success of Android, which facilitate the fast development of Android applications. Detecting TPLs in Android apps is also important for downstream tasks, such as malware and repackaged apps identification. To identify in-app TPLs, we need to solve several challenges, such as TPL dependency, code obfuscation, precise Version representation. Unfortunately, existing TPL Detection tools have been proved that they have not solved these challenges very well, let alone specify the exact TPL Versions. To this end, we propose a system, named ATVHunter, which can pinpoint the precise vulnerable in-app TPL Versions and provide detailed information about the vulnerabilities and TPLs. We propose a two-phase Detection approach to identify specific TPL Versions. Specifically, we extract the Control Flow Graphs as the coarse-grained feature to match potential TPLs in the pre-defined TPL database, and then extract opcode in each basic block of CFG as the fine-grained feature to identify the exact TPL Versions. We build a comprehensive TPL database (189,545 unique TPLs with 3,006,676 Versions) as the reference database. Meanwhile, to identify the vulnerable in-app TPL Versions, we also construct a comprehensive and known vulnerable TPL database containing 1,180 CVEs and 224 security bugs. Experimental results show AtVHunter outperforms state-of-the-art TPL Detection tools, achieving 90.55% precision and 88.79% recall with high efficiency, and is also resilient to widely-used obfuscation techniques and scalable for large-scale TPL Detection. Furthermore, to investigate the ecosystem of the vulnerable TPLs used by apps, we exploit newtool to conduct a large-scale analysis on 104,446 apps and find that 9,050 apps include vulnerable TPL Versions with 53,337 vulnerabilities and 7,480 security bugs, most of which are with high risks and are not recognized by app developers.
Lingling Fan - One of the best experts on this subject based on the ideXlab platform.
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atvhunter reliable Version Detection of third party libraries for vulnerability identification in android applications
International Conference on Software Engineering, 2021Co-Authors: Xian Zhan, Lingling Fan, Sen Chen, Tianming Liu, Xiapu Luo, Yang LiuAbstract:Third-party libraries (TPLs) as essential parts in the mobile ecosystem have become one of the most significant contributors to the huge success of Android, which facilitate the fast development of Android applications. Detecting TPLs in Android apps is also important for downstream tasks, such as malware and repackaged apps identification. To identify in-app TPLs, we need to solve several challenges, such as TPL dependency, code obfuscation, precise Version representation. Unfortunately, existing TPL Detection tools have been proved that they have not solved these challenges very well, let alone specify the exact TPL Versions. To this end, we propose a system, named ATVHunter, which can pinpoint the precise vulnerable in-app TPL Versions and provide detailed information about the vulnerabilities and TPLs. We propose a two-phase Detection approach to identify specific TPL Versions. Specifically, we extract the Control Flow Graphs as the coarse-grained feature to match potential TPLs in the pre-defined TPL database, and then extract opcode in each basic block of CFG as the fine-grained feature to identify the exact TPL Versions. We build a comprehensive TPL database (189,545 unique TPLs with 3,006,676 Versions) as the reference database. Meanwhile, to identify the vulnerable in-app TPL Versions, we also construct a comprehensive and known vulnerable TPL database containing 1,180 CVEs and 224 security bugs. Experimental results show AtVHunter outperforms state-of-the-art TPL Detection tools, achieving 90.55% precision and 88.79% recall with high efficiency, and is also resilient to widely-used obfuscation techniques and scalable for large-scale TPL Detection. Furthermore, to investigate the ecosystem of the vulnerable TPLs used by apps, we exploit newtool to conduct a large-scale analysis on 104,446 apps and find that 9,050 apps include vulnerable TPL Versions with 53,337 vulnerabilities and 7,480 security bugs, most of which are with high risks and are not recognized by app developers.
Sen Chen - One of the best experts on this subject based on the ideXlab platform.
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atvhunter reliable Version Detection of third party libraries for vulnerability identification in android applications
International Conference on Software Engineering, 2021Co-Authors: Xian Zhan, Lingling Fan, Sen Chen, Tianming Liu, Xiapu Luo, Yang LiuAbstract:Third-party libraries (TPLs) as essential parts in the mobile ecosystem have become one of the most significant contributors to the huge success of Android, which facilitate the fast development of Android applications. Detecting TPLs in Android apps is also important for downstream tasks, such as malware and repackaged apps identification. To identify in-app TPLs, we need to solve several challenges, such as TPL dependency, code obfuscation, precise Version representation. Unfortunately, existing TPL Detection tools have been proved that they have not solved these challenges very well, let alone specify the exact TPL Versions. To this end, we propose a system, named ATVHunter, which can pinpoint the precise vulnerable in-app TPL Versions and provide detailed information about the vulnerabilities and TPLs. We propose a two-phase Detection approach to identify specific TPL Versions. Specifically, we extract the Control Flow Graphs as the coarse-grained feature to match potential TPLs in the pre-defined TPL database, and then extract opcode in each basic block of CFG as the fine-grained feature to identify the exact TPL Versions. We build a comprehensive TPL database (189,545 unique TPLs with 3,006,676 Versions) as the reference database. Meanwhile, to identify the vulnerable in-app TPL Versions, we also construct a comprehensive and known vulnerable TPL database containing 1,180 CVEs and 224 security bugs. Experimental results show AtVHunter outperforms state-of-the-art TPL Detection tools, achieving 90.55% precision and 88.79% recall with high efficiency, and is also resilient to widely-used obfuscation techniques and scalable for large-scale TPL Detection. Furthermore, to investigate the ecosystem of the vulnerable TPLs used by apps, we exploit newtool to conduct a large-scale analysis on 104,446 apps and find that 9,050 apps include vulnerable TPL Versions with 53,337 vulnerabilities and 7,480 security bugs, most of which are with high risks and are not recognized by app developers.
Tianming Liu - One of the best experts on this subject based on the ideXlab platform.
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atvhunter reliable Version Detection of third party libraries for vulnerability identification in android applications
International Conference on Software Engineering, 2021Co-Authors: Xian Zhan, Lingling Fan, Sen Chen, Tianming Liu, Xiapu Luo, Yang LiuAbstract:Third-party libraries (TPLs) as essential parts in the mobile ecosystem have become one of the most significant contributors to the huge success of Android, which facilitate the fast development of Android applications. Detecting TPLs in Android apps is also important for downstream tasks, such as malware and repackaged apps identification. To identify in-app TPLs, we need to solve several challenges, such as TPL dependency, code obfuscation, precise Version representation. Unfortunately, existing TPL Detection tools have been proved that they have not solved these challenges very well, let alone specify the exact TPL Versions. To this end, we propose a system, named ATVHunter, which can pinpoint the precise vulnerable in-app TPL Versions and provide detailed information about the vulnerabilities and TPLs. We propose a two-phase Detection approach to identify specific TPL Versions. Specifically, we extract the Control Flow Graphs as the coarse-grained feature to match potential TPLs in the pre-defined TPL database, and then extract opcode in each basic block of CFG as the fine-grained feature to identify the exact TPL Versions. We build a comprehensive TPL database (189,545 unique TPLs with 3,006,676 Versions) as the reference database. Meanwhile, to identify the vulnerable in-app TPL Versions, we also construct a comprehensive and known vulnerable TPL database containing 1,180 CVEs and 224 security bugs. Experimental results show AtVHunter outperforms state-of-the-art TPL Detection tools, achieving 90.55% precision and 88.79% recall with high efficiency, and is also resilient to widely-used obfuscation techniques and scalable for large-scale TPL Detection. Furthermore, to investigate the ecosystem of the vulnerable TPLs used by apps, we exploit newtool to conduct a large-scale analysis on 104,446 apps and find that 9,050 apps include vulnerable TPL Versions with 53,337 vulnerabilities and 7,480 security bugs, most of which are with high risks and are not recognized by app developers.
