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US Patent 10521587 Detecting code obfuscation using recurrent neural networks

OverviewStructured DataIssuesContributorsActivity
Is a
Patent
Patent
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Date Filed
July 31, 2017
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Date of Patent
December 31, 2019
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Patent Application Number
15665330
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Patent Citations Received
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US Patent 12111925 Methods and apparatus for detecting and preventing obfuscated cyberattacks using machine learning techniques
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US Patent 11397742 Rescaling layer in neural network
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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 11966477 Methods and apparatus for generic process chain entity mapping
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US Patent 12010129 Methods and apparatus for using machine learning to classify malicious infrastructure
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US Patent 11574052 Methods and apparatus for using machine learning to detect potentially malicious obfuscated scripts
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US Patent 11017177 Neural network systems and methods for target identification from text
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US Patent 11620379 Methods and apparatus for detecting and preventing obfuscated cyberattacks using machine learning techniques
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US Patent 11609991 Methods and apparatus for using machine learning on multiple file fragments to identify malware
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•••
Patent Inventor Names
Arie Agranonik
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Zohar Duchin
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
10521587
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Patent Primary Examiner
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Wasika Nipa
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