Explore effective vulnerability discovery techniques using machine learning in this 27-minute Black Hat conference talk. Delve into Software Composition Analysis (SCA) and its role in identifying vulnerabilities in third-party dependencies. Learn about the challenges faced by central authorities in maintaining vulnerability databases and how machine learning can enhance the process. Examine data examples and key observations presented by Ming Yi Ang and Asankhaya Sharma. Gain insights into modern software composition, external dependencies, and the evolving landscape of vulnerability discovery.
Effective Vulnerability Discovery with Machine Learning
Overview
Syllabus
Introduction
Overview
Machine Learning Approach
External Dependencies
Modern Software Composition
Central Authorities
Challenges
Data Examples
Key Observations
Conclusion
Taught by
Black Hat
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