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US Patent 10193902 Methods and systems for malware detection

Patent 10193902 was granted and assigned to Deep Instinct on January, 2019 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Deep Instinct
Deep Instinct
Current Assignee
Deep Instinct
Deep Instinct
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10193902
Patent Inventor Names
Nadav Maman0
Yoel Neeman0
Doron Cohen0
Eli David0
Guy Caspi0
Ishai Rosenberg0
Date of Patent
January 29, 2019
Patent Application Number
14929902
Date Filed
November 2, 2015
Patent Citations Received
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US Patent 12130943 Generative artificial intelligence model personally identifiable information detection and protection
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US Patent 11941121 Systems and methods for detecting malware using static and dynamic malware models
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US Patent 11941124 Systems and methods for detecting malware using static and dynamic malware models
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US Patent 11947668 Methods and apparatus for preserving information between layers within a neural network
0
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US Patent 12003522 Method and system for adaptive network intrusion detection
0
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US Patent 12010129 Methods and apparatus for using machine learning to classify malicious infrastructure
0
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US Patent 12107885 Prompt injection classifier using intermediate results
0
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US Patent 12105844 Selective redaction of personally identifiable information in generative artificial intelligence model outputs
0
...
Patent Primary Examiner
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Hadi S Armouche
Patent abstract

According to some embodiments, a method for training a malware detector comprising a deep learning algorithm is described, which comprises converting a set of malware files and non malware files into vectors by using a feature based dictionary, and/or by using a conversion into an image, and providing prospects that the files constitute malware. Various features and combinations of features are described to build a feature based dictionary and adapt its size. According to some embodiments, a method for detecting a malware by using a malware detector comprising a deep learning algorithm is described, which comprises converting a file into a vector by using a feature based dictionary, and/or by using a conversion into an image, and providing prospects that the file constitutes malware. Methods for providing a plurality of prospects and aggregating these prospects are provided. Additional methods and systems in the field of malware detection are also described.

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