Anomalicious: Automated Detection of Anomalous and Potentially Malicious Commits on GitHub-Reference-Cited by-同舟云学术

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Anomalicious: Automated Detection of Anomalous and Potentially Malicious Commits on GitHub

Published:2021-05 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)
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Author:

Gonzalez Danielle,Zimmermann Thomas,Godefroid Patrice,Schaefer Max

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9401806/9401954/09402087.pdf?arnumber=9402087

Cited by 19 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. Software supply chain security: a systematic literature review;International Journal of Computers and Applications;2024-08-19

2. Malicious Package Detection using Metadata Information;Proceedings of the ACM Web Conference 2024;2024-05-13

3. PAVUDI: Patch-based Vulnerability Discovery using Machine Learning;Annual Computer Security Applications Conference;2023-12-04

4. On the Feasibility of Cross-Language Detection of Malicious Packages in npm and PyPI;Annual Computer Security Applications Conference;2023-12-04

5. Construction of Software Supply Chain Threat Portrait Based on Chain Perspective;Mathematics;2023-12-02

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