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AUTOMATED DETECTION OF MALWARE USING TRAINED NEURAL NETWORK-BASED FILE CLASSIFIERS AND MACHINE LEARNING
AUTOMATED DETECTION OF MALWARE USING TRAINED NEURAL NETWORK-BASED FILE CLASSIFIERS AND MACHINE LEARNING
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机译:使用经过训练的基于神经网络的文件分类器和机器学习来自动检测恶意软件
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摘要
Automated malware detection for application file packages using machine learning (e.g., trained neural network-based classifiers) is described. A particular method includes generating, at a first device, a first feature vector based on occurrences of character n-grams corresponding to a first subset of files of multiple files of an application file package. The method includes generating, at the first device, a second feature vector based on occurrences of attributes in a second subset of files of the multiple files. The method includes sending the first feature vector and the second feature vector from the first device to a second device as inputs to a file classifier. The method includes receiving, at the first device from the second device, classification data associated with the application file package based on the first feature vector and the second feature vector. The classification data indicates whether the application file package includes malware.
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