Detecting and Measuring Misconfigured Manifests in Android Apps

Author:

Yang Yuqing1,Elsabagh Mohamed2,Zuo Chaoshun1,Johnson Ryan2,Stavrou Angelos2,Lin Zhiqiang1

Affiliation:

1. The Ohio State University, Columbus, OH, USA

2. Quokka, McLean, VA, USA

Funder

NSF (National Science Foundation)

Publisher

ACM

Reference54 articles.

1. 2017. CVE-2017--16835. https://nvd.nist.gov/vuln/detail/CVE-2017-16835. (Ac- cessed on 2021-01-18). 2017. CVE-2017--16835. https://nvd.nist.gov/vuln/detail/CVE-2017-16835. (Ac- cessed on 2021-01-18).

2. 2017. CVE-2017-17551. https://nvd.nist.gov/vuln/detail/CVE-2017-17551. (Accessed on 2021-01-18). 2017. CVE-2017-17551. https://nvd.nist.gov/vuln/detail/CVE-2017-17551. (Accessed on 2021-01-18).

3. 2021. Android manifest development documents. https://developer.android.com/ guide/topics/manifest/manifest-intro. (Accessed on 2021-01-18). 2021. Android manifest development documents. https://developer.android.com/ guide/topics/manifest/manifest-intro. (Accessed on 2021-01-18).

4. 2021. Android Open Source Project. https://cs.android.com/android/platform/ superproject. 2021. Android Open Source Project. https://cs.android.com/android/platform/ superproject.

5. 2021. Android Package Parser. http://androidxref.com/9.0.0_r3/xref/frameworks/ base/core/java/android/content/pm/PackageParser.java#parseVerifier. (Accessed on 2021-01-12). 2021. Android Package Parser. http://androidxref.com/9.0.0_r3/xref/frameworks/ base/core/java/android/content/pm/PackageParser.java#parseVerifier. (Accessed on 2021-01-12).

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MLCAC: Dynamic Authorization and Intelligent Decision-making towards Insider Threats;2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD);2024-05-08

2. Poster: Privacy Risks from Misconfigured Android Content Providers;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

3. "Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

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