133 citations · 195 across the 6 of their papers we have counts for
3 papers · 1 filter
Efficient Malware Analysis Using Metric Embeddings
Ethan M. Rudd, David Krisiloff, Scott Coull +3
In this paper, we explore the use of metric learning to embed Windows PE files in a low-dimensional vector space for downstream use in a variety of applications, including malware…
Activation Analysis of a Byte-Based Deep Neural Network for Malware Classification
Scott E. Coull, Christopher Gardner
Feature engineering is one of the most costly aspects of developing effective machine learning models, and that cost is even greater in specialized problem domains, like malware cl…
Exploring Adversarial Examples in Malware Detection
Octavian Suciu, Scott E. Coull, Jeffrey Johns
The convolutional neural network (CNN) architecture is increasingly being applied to new domains, such as malware detection, where it is able to learn malicious behavior from raw b…