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METHODS AND APPARATUS FOR DETECTING AND IDENTIFYING MALWARE BY MAPPING FEATURE DATA INTO A SEMANTIC SPACE
METHODS AND APPARATUS FOR DETECTING AND IDENTIFYING MALWARE BY MAPPING FEATURE DATA INTO A SEMANTIC SPACE
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机译:通过将特征数据映射到语义空间中来检测和识别恶意软件的方法和装置
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摘要
In some embodiments, an apparatus includes a memory and a processor operatively coupled to the memory. The processor is configured to identify a feature vector for a potentially malicious file and provide the feature vector as an input to a trained neural network autoencoder to produce a modified feature vector. The processor is configured to generate an output vector by introducing Gaussian noise into the modified feature vector to ensure a Gaussian distribution for the output vector within a set of modified feature vectors. The processor is configured to provide the output vector as an input to a trained neural network decoder associated with the trained neural network autoencoder to produce an identifier of a class associated with the set of modified feature vectors. The processor is configured to perform a remedial action on the potentially malicious file based on the potentially malicious file being associated with the class.
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