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US Patent 11341235 Anomaly detection with adaptive auto grouping

Patent 11341235 was granted and assigned to Raytheon on May, 2022 by the United States Patent and Trademark Office.

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TimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Applicant
Raytheon
Raytheon
Current Assignee
Raytheon
Raytheon
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11341235
Date of Patent
May 24, 2022
Patent Application Number
16281922
Date Filed
February 21, 2019
Patent Citations
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US Patent 10507973 Foldable container
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US Patent 10521584 Computer threat analysis service
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US Patent 10937465 Anomaly detection with reduced memory overhead
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US Patent 10929722 Anomaly detection in streaming networks
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US Patent 11036858 System and method for training a model for detecting malicious objects on a computer system
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US Patent 11132923 Encryption using spatial voting
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US Patent 10076273 Real-time monitoring and control of physical and arousal status of individual organisms
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US Patent 10110629 Managed honeypot intrusion detection system
...
Patent Citations Received
‌
US Patent 11841942 Anomaly detection device and anomaly detection method
12
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US Patent 11507847 Gene expression programming
‌
US Patent 11777818 Drift resolver for enterprise applications
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US Patent 11463462 Bot behavior detection
Patent Primary Examiner
‌
Paul E Callahan
CPC Code
‌
G06F 21/554
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G06F 21/556
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G06F 21/552
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G06F 21/54

A method of identifying anomalous behavior can include determining a first feature value and a second feature value of a series of numbers, identifying whether the determined first and second feature values map to a cell that is a part of a group based on spatial voting (SV) grid data, the SV grid data indicating an extent of each cell in a grid of cells, a number of rows and columns of cells in a group of cells, and, for each group of cells, a point in the center cell of the group of cells and a unique group number, and in response to identifying that the determined first and second feature values do not map to a cell of the grid of cells that is a part of a group, tagging the first and second feature values as corresponding to an anomalous behavior.

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