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    THREAT REGISTRY AND ASSESSMENT
    3.
    发明申请
    THREAT REGISTRY AND ASSESSMENT 有权

    公开(公告)号：US20250030716A1

    公开(公告)日：2025-01-23

    申请号：US17194768

    申请日：2021-03-08

    Applicant: Wells Fargo Bank, N.A.

    Inventor： Shane Dale Cross ,  Peter Anatole Makohon ,  Christopher Schooley ,  Shawn Wallis ,  Robert Irving Kirby, JR. ,  Jae Wook Lee

    IPC: H04L29/06

    Abstract: Techniques described herein pertain to prioritizing threats based on their potential effect on the specific enterprise network sought to be protected. In one example, this disclosure describes a method that includes collecting, by a computing system and from a plurality of external data sources, threat information; storing, by the computing system and in a threat registry, the threat information that includes information about a plurality of threats; collecting, by the computing system, information about an attack surface for an enterprise network; mapping, by the computing system, the threat information to the attack surface; analyzing, by the computing system and based on the mapping of the threat information to the attack surface, a threat included in the plurality of threats to identify a risk score associated with the threat, wherein the risk score represents an assessment of the vulnerability of the enterprise network to the threat.

    Autonomous configuration modeling and management
    7.
    发明授权
    Autonomous configuration modeling and management 有权

    公开(公告)号：US11522898B1

    公开(公告)日：2022-12-06

    申请号：US16222105

    申请日：2018-12-17

    Applicant: Wells Fargo Bank, N.A.

    Inventor： Lawrence T. Belton, Jr. ,  Jon M. Welborn ,  Gary Simms, Sr. ,  Peter Anatole Makohon ,  Jacob Lee

    IPC: H04L29/06 ,  H04L9/40 ,  G06N20/00 ,  G06K9/62 ,  G06N5/02

    Abstract: The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods of autonomous asset configuration modeling and management. The innovation includes probing elements of a networked architecture to compile information about elements in the networked architecture. The innovation learns a configuration for the at least one element in the environment based on the probing and determines vulnerabilities in the learned configuration. The innovation develops a threat model based on the learned configuration. The innovation applies the threat model to the elements of the networked architecture and deploys a configuration that resolves the vulnerabilities based on the threat model to the elements in the networked architecture. The threat model can be developed over time using machine learning concepts and deep learning of data sources associated with the elements and vulnerabilities.

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