DATA-DRIVEN IDENTIFICATION OF MALICIOUS FILES USING MACHINE LEARNING AND AN ENSEMBLE OF MALWARE DETECTION PROCEDURES

Techniques are provided for data-driven ensemble-based malware detection. An exemplary method comprises obtaining a file; extracting metadata from the file; obtaining a plurality of malware detection procedures; selecting a subset of the plurality of malware detection procedures to apply to the file utilizing a likelihood that each of the plurality of malware detection procedures will result in a malware detection for the file based on the extracted metadata; applying the selected subset of the malware detection procedures to the file; and processing results of the subset of malware detection procedures using a machine learning model to determine a probability of the file being malware.