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US Patent 11303653 Network threat detection and information security using machine learning

OverviewStructured DataIssuesContributors

Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Current Assignee
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11303653
Date of Patent
April 12, 2022
Patent Application Number
16538549
Date Filed
August 12, 2019
Patent Citations
‌
US Patent 10122743 Methods and systems for detecting anomalous behavior of network-connected embedded devices
‌
US Patent 10169135 Computer system and method of detecting manufacturing network anomalies
‌
US Patent 10193913 Joint anomaly detection across IOT devices
‌
US Patent 10320824 Anomaly detection using network traffic data
‌
US Patent 10440037 Identifying malware-suspect end points through entropy changes in consolidated logs
‌
US Patent 10462116 Detection of data exfiltration
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US Patent 10635813 Methods and apparatus for using machine learning on multiple file fragments to identify malware
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US Patent 10664619 Automated agent for data copies verification
...
Patent Primary Examiner
‌
Badri Narayanan Champakesan
CPC Code
‌
H04L 63/1425
‌
H04L 63/145
‌
H04L 63/1416
‌
G06N 20/00
‌
G06N 3/08
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H04L 63/1491
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H04L 63/1466

An information security system that includes an information security engine configured to monitor data transmissions within a network and to detect a first attack by a malicious software element. The information security engine is further configured to detect a second attack by the malicious software element within a predetermined time interval from the first attack and to transfer the malicious software element from the network to an emulated network in response to detecting the second attack. The information security engine is further configured to generate an attack log comprising behavior characteristics for attacks performed by the malicious software element in the emulated network and to train a machine learning model based on behavior characteristics from the attack log.

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