Decoding the Secrets of Machine Learning in Malware Classification: A Deep Dive into Datasets, Feature Extraction, and Model Performance

1 code implementation • 27 Jul 2023 • Savino Dambra, Yufei Han, Simone Aonzo, Platon Kotzias, Antonino Vitale, Juan Caballero, Davide Balzarotti, Leyla Bilge

As a consequence, our community still lacks an understanding of malware classification results: whether they are tied to the nature and distribution of the collected dataset, to what extent the number of families and samples in the training dataset influence performance, and how well static and dynamic features complement each other.

Classification Malware Detection

"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice

no code implementations • 29 Dec 2022 • Giovanni Apruzzese, Hyrum S. Anderson, Savino Dambra, David Freeman, Fabio Pierazzi, Kevin A. Roundy

Recent years have seen a proliferation of research on adversarial machine learning.