A machine learning approach for vulnerability curation

• Main Authors: CHEN, Yang, SANTOSA, Andrew E., ANG, Ming Yi, SHARMA, Abhishek, SHARMA, Asankhaya, LO, David
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: application security; open-source software; machine learning; classifiers ensemble; self-training; Artificial Intelligence and Robotics; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/5627; https://ink.library.smu.edu.sg/context/sis_research/article/6630/viewcontent/A_Machine_Learning_Approach_for_Vulnerability_Curation.pdf
• Institution: Singapore Management University

Software composition analysis depends on database of open-source library vulerabilities, curated by security researchers using various sources, such as bug tracking systems, commits, and mailing lists. We report the design and implementation of a machine learning system to help the curation by by au...