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US Patent 12132753 Enhanced network security based on inter-application data flow diagrams

Patent 12132753 was granted and assigned to Bank of America 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
Bank of America
Bank of America
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Current Assignee
Bank of America
Bank of America
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
121327530
Patent Inventor Names
David Mortman0
Adam B. Richman0
Jack Bishop, III0
Date of Patent
October 29, 2024
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Patent Application Number
170212620
Date Filed
September 15, 2020
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Patent Citations
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US Patent 7286854 Method for configuring a communication network, related network architecture and computer program product therefor
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US Patent 6839680 Internet profiling
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US Patent 6937493 Programming flash memory via a boundary scan register
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US Patent 6965938 System and method for clustering servers for performance and load balancing
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US Patent 7130807 Technology sharing during demand and supply planning in a network-based supply chain environment
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US Patent 7281015 Method and apparatus for providing an interface between system architect and OPNET
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US Patent 10270796 Data protection analytics in cloud computing platform
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US Patent 10341374 Systems and methods detecting and mitigating anomalous shifts in a machine learning model
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Patent Primary Examiner
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Melvin H Pollack
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CPC Code
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G06F 11/302
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G06F 9/547
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G06F 16/2379
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G06N 20/00
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H04L 63/1433
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Patent abstract

Aspects of the disclosure relate to enhanced network security based on inter-application data flows. A computing platform may monitor, via application programming interfaces, data transmissions between applications. Subsequently, the computing platform may retrieve one or more of a time of the data transmission, a source of the data transmission, and a destination of the data transmission. Then, the computing platform may generate a structured database where a pair of components of the database are dynamically linked to one another when the pair of components corresponds to a source and a destination for a data transmission. Subsequently, the computing platform may train a machine learning model to detect structural patterns within the structured database. Then, the computing platform may generate clusters indicative of similar application profiles. Then, the computing platform may predict an impact of a change in an application profile of an application of the plurality of applications.

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