Neural attention mechanisms for malware analysis
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United States of America Patent
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Aug 1, 2017
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app pub date -
Jul 21, 2016
filing date -
Jul 21, 2016
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Abstract
As part of an analysis of the likelihood that a given input (e.g. a file, etc.) includes malicious code, a convolutional neural network can be used to review a sequence of chunks into which an input is divided to assess how best to navigate through the input and to classify parts of the input in a most optimal manner. At least some of the sequence of chunks can be further examined using a recurrent neural network in series with the convolutional neural network to determine how to progress through the sequence of chunks. A state of the at least some of the chunks examined using the recurrent neural network summarized to form an output indicative of the likelihood that the input includes malicious code. Methods, systems, and articles of manufacture are also described.
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