Among many initiatives, Google awards research work in promising fields developed in Latin America. Fabricio’s work was awarded in the machine learning category and proposed detecting concept drift in malware classifier. Concept drift is the name of the phenomenon which causes classifier’s accuracy to be reduced due to changes in the definition (characteristics) of classified object. SECRET have been working in concept drift because malware samples are very dynamic objects, thus
causing malware classifiers to drift and reduce their detection capabilities. Fabricio’s evaluation of a dataset of Brazilian malware samples highlighted the need of considering concept drift in long-term malware detection routines and resulted in a paper published in IEEE S&P magazine (Check it here).