Are Machine Learning Models for Malware Detection Ready for Prime Time?
Lorenzo Cavallaro, Johannes Kinder, Feargus Pendlebury, Fabio Pierazzi
Abstract
We investigate why the performance of machine learning models for malware detection observed in a lab setting often cannot be reproduced in practice. We discuss how to set up experiments mimicking a practical deployment and how to measure the robustness of a model over time.
Topics & Concepts
MalwareRobustness (evolution)Software deploymentComputer scienceMachine learningArtificial intelligenceComputer securitySoftware engineeringGeneBiochemistryChemistryAdvanced Malware Detection TechniquesNetwork Security and Intrusion DetectionAnomaly Detection Techniques and Applications