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US Patent 11522881 Structural graph neural networks for suspicious event detection

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Patent
Patent
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Patent attributes

Patent Applicant
Nec Laboratories America, Inc.
Nec Laboratories America, Inc.
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
115228810
Patent Inventor Names
Zhengzhang Chen0
Haifeng Chen0
Jiaping Gui0
Lei Cai0
Date of Patent
December 6, 2022
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Patent Application Number
169923950
Date Filed
August 13, 2020
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Patent Citations
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US Patent 11363028 Systems and methods for delegating access to a protected resource
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US Patent 10810210 Performance and usability enhancements for continuous subgraph matching queries on graph-structured data
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US Patent 10484402 Security in virtualized computing environments
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US Patent 10511613 Knowledge transfer system for accelerating invariant network learning
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US Patent 10599550 Systems and methods to identify breaking application program interface changes
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US Patent 10685293 Methods and systems for analyzing cybersecurity threats
Patent Primary Examiner
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Viral S Lakhia
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CPC Code
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H04L 63/1416
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G06N 3/08
0

A computer-implemented method for graph structure based anomaly detection on a dynamic graph is provided. The method includes detecting anomalous edges in the dynamic graph by learning graph structure changes in the dynamic graph with respect to target edges to be evaluated in a given time window repeatedly applied to the dynamic graph. The target edges correspond to particular different timestamps. The method further includes predicting a category of each of the target edges as being one of anomalous and non-anomalous based on the graph structure changes. The method also includes controlling a hardware based device to avoid an impending failure responsive to the category of at least one of the target edges.

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