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

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

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.
机译:提供了用于基于数据驱动的基于集成的恶意软件检测的技术。一种示例性方法包括获得文件;以及从文件中提取元数据;获取多个恶意软件检测过程;基于所提取的元数据,利用多个恶意软件检测过程中的每一个将导致文件的恶意软件检测的可能性,选择多个恶意软件检测过程的子集以应用于文件。将选定的恶意软件检测过程子集应用于文件;使用机器学习模型确定和处理恶意软件检测过程的子集的结果,以确定文件为恶意软件的可能性。

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