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US Patent 11930025 Threat detection and prevention for information systems

Patent 11930025 was granted and assigned to Bank of America on March, 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
119300250
Patent Inventor Names
Daniel Joseph Serna0
Christopher Lee Danielson0
Marcus Raphael Matos0
Patrick N. Lawrence0
Date of Patent
March 12, 2024
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Patent Application Number
172314560
Date Filed
April 15, 2021
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Patent Citations
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US Patent 8955138 Systems and methods for reevaluating apparently benign behavior on computing devices
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US Patent 9047464 Continuous monitoring of computer user and computer activities
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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 7506371 System and methods for adaptive behavior based access control
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US Patent 8056130 Real time monitoring and analysis of events from multiple network security devices
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US Patent 8356001 Systems and methods for application-level security
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US Patent 8793790 System and method for insider threat detection
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US Patent 8856936 Pervasive, domain and situational-aware, adaptive, automated, and coordinated analysis and control of enterprise-wide computers, networks, and applications for mitigation of business and operational risks and enhancement of cyber security
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Patent Primary Examiner
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Joseph P Hirl
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CPC Code
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G06N 20/00
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H04L 63/0263
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G06N 3/08
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H04L 63/1425
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H04L 63/0236
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Patent abstract

A device that is configured to receive user activity information that includes information about user interactions with a network device for a plurality of users. The device is further configured to input the user activity information into a first machine learning model that is configured to receive user activity information and to output a set of bad actor candidates based on the user activity information. The device is further configured to filter the user activity information based on the set of bad actor candidates. The device is further configured to input the filtered user activity information into a second machine learning model that is configured to receive the filtered user activity information and to output system exposure information that identifies network security threats. The device is further configured to identify network security actions based on the network security threats and to execute the network security actions.

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