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US Patent 9721097 Neural attention mechanisms for malware analysis

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Is a
Patent
Patent

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
9721097
Date of Patent
August 1, 2017
Patent Application Number
15216661
Date Filed
July 21, 2016
Patent Citations Received
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US Patent 12010129 Methods and apparatus for using machine learning to classify malicious infrastructure
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US Patent 11935296 Apparatus and method for online action detection
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US Patent 11941491 Methods and apparatus for identifying an impact of a portion of a file on machine learning classification of malicious content
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US Patent 11947668 Methods and apparatus for preserving information between layers within a neural network
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US Patent 11711388 Automated detection of malware using trained neural network-based file classifiers and machine learning
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US Patent 11785024 Deploying neural-trojan-resistant convolutional neural networks
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US Patent 11888872 Protecting computer assets from malicious attacks
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US Patent 11916937 System and method for information gain for malware detection
0
...
Patent Primary Examiner
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Kendall Dolly
Patent 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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