Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data

1 code implementation • 21 Dec 2020 • Aayush Garg, Renzo Degiovanni, Matthieu Jimenez, Maxime Cordy, Mike Papadakis, Yves Le Traon

To tackle these issues, we propose TROVON, a technique that learns from known vulnerable components rather than from vulnerable and non-vulnerable components, as typically performed.

Machine Translation Cryptography and Security Software Engineering