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US Patent 12131265 Enhancement of machine learning-based anomaly detection using knowledge graphs

Patent 12131265 was granted and assigned to EBay on October, 2024 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
EBay
EBay
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Current Assignee
EBay
EBay
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
121312650
Patent Inventor Names
Phuong Nguyen0
Hanzhang Wang0
Date of Patent
October 29, 2024
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Patent Application Number
179772400
Date Filed
October 31, 2022
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Patent Citations
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US Patent 9031951 Associating interest and disinterest keywords with similar and dissimilar users
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US Patent 9141790 Systems and methods for using event-correlation graphs to detect attacks on computing systems
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US Patent 9298525 Adaptive fault diagnosis
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US Patent 9609011 Interface having selectable, interactive views for evaluating potential network compromise
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US Patent 9736173 Differential dependency tracking for attack forensics
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US Patent 9836183 Summarized network graph for semantic similarity graphs of large corpora
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US Patent 10205735 Graph-based network security threat detection across time and entities
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US Patent 10409910 Perceptual associative memory for a neuro-linguistic behavior recognition system
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Patent Primary Examiner
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Michael Won
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CPC Code
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G06N 5/022
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G06F 16/9024
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G06N 20/00
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G06N 5/04
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Patent abstract

Technologies are disclosed herein for enhancing machine learning (“ML”)-based anomaly detection systems using knowledge graphs. The disclosed technologies generate a connected graph that defines a topology of infrastructure components along with associated alarms generated by a ML component. The ML component generates the alarms by applying ML techniques to real-time data metrics generated by the infrastructure components. Scores are computed for the infrastructure components based upon the connected graph. A root cause of an anomaly affecting infrastructure components can then be identified based upon the scores, and remedial action can be taken to address the root cause of the anomaly. A user interface is also provided for visualizing aspects of the connected graph.

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