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DATA-DRIVEN IDENTIFICATION OF MALICIOUS FILES USING MACHINE LEARNING AND AN ENSEMBLE OF MALWARE DETECTION PROCEDURES
DATA-DRIVEN IDENTIFICATION OF MALICIOUS FILES USING MACHINE LEARNING AND AN ENSEMBLE OF MALWARE DETECTION PROCEDURES
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机译:使用机器学习和恶意软件检测程序进行数据驱动的恶意文件识别
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摘要
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.
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