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US Patent 11836664 Enterprise network threat detection

Patent 11836664 was granted and assigned to Sophos on December, 2023 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
Sophos Group PLC
Sophos Group PLC
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Current Assignee
Sophos Group PLC
Sophos Group PLC
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
118366640
Patent Inventor Names
Mark Anthony Russo0
Russell Humphries0
Karl Ackerman0
Andrew J. Thomas0
Date of Patent
December 5, 2023
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Patent Application Number
168966760
Date Filed
June 9, 2020
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Patent Citations
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US Patent 8201243 Backwards researching activity indicative of pestware
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US Patent 8418250 Methods and apparatus for dealing with malware
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US Patent 8607347 Network stream scanning facility
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US Patent 8719932 Backwards researching activity indicative of pestware
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US Patent 8726389 Methods and apparatus for dealing with malware
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US Patent 8763123 Methods and apparatus for dealing with malware
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US Patent 8779921 Adaptive security network, sensor node and method for detecting anomalous events in a security network
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US Patent 8805995 Capturing data relating to a threat
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Patent Citations Received
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US Patent 12003426 Multi-tier resource, subsystem, and load orchestration
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Patent Primary Examiner
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Nicholas Augustine
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CPC Code
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H04L 63/20
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H04L 63/1441
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G06F 16/955
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G06F 9/542
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G06F 11/079
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G06F 17/18
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G06F 21/554
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G06F 21/56
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Patent abstract

In a threat management platform, a number of endpoints log events in an event data recorder. A local agent filters this data and feeds a filtered data stream to a central threat management facility. The central threat management facility can locally or globally tune filtering by local agents based on the current data stream, and can query local event data recorders for additional information where necessary or helpful in threat detection or forensic analysis. The central threat management facility also stores and deploys a number of security tools such as a web-based user interface supported by machine learning models to identify potential threats requiring human intervention and other models to provide human-readable context for evaluating potential threats.

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