VERIFYING TRUSTED COMMUNICATIONS USING ESTABLISHED COMMUNICATION CHANNELS

    公开(公告)号:US20220103539A1

    公开(公告)日:2022-03-31

    申请号:US17036756

    申请日:2020-09-29

    Abstract: In various examples, communications from a host device—which may be associated with an entity—and to a client device may be are verified through established channels of communication. Systems and methods are disclosed that use authentication signals and notifications, which may include predetermined passwords and time-sensitive values, to facilitate verification of the communication between the host device and client device. The notifications may be delivered using applications or web-based applications that are associated with an entity. Once the communication has been verified as trusted, the host device and/or the client device may present notifications that the communication is verified as trusted. The notifications may be presented using audio, video, and/or haptic methods.

    APPLICATION FIREWALLS BASED ON SELF-MODELING SERVICE FLOWS

    公开(公告)号:US20210234833A1

    公开(公告)日:2021-07-29

    申请号:US16773322

    申请日:2020-01-27

    Abstract: In various examples, firewalls may include machine learning models that are automatically trained and applied to analyze service inputs submitted to input processing services and to identify whether service inputs are desirable (e.g., will result in an undesirable status code if processed by a service). When a service input is determined by a firewall to be desirable, the firewall may push the service input through to the input processing service for normal processing. When a service input is determined by the firewall to be undesirable, the firewall may block or drop the service input before it reaches the input processing service and/or server. This may be used to prevent the service input, which is likely to be undesirable, from touching a server that hosts the input processing service (e.g., preventing a crash).

    Application firewalls based on self-modeling service flows

    公开(公告)号:US11831608B2

    公开(公告)日:2023-11-28

    申请号:US16773322

    申请日:2020-01-27

    CPC classification number: H04L63/0245 G06N20/00

    Abstract: In various examples, firewalls may include machine learning models that are automatically trained and applied to analyze service inputs submitted to input processing services and to identify whether service inputs are desirable (e.g., will result in an undesirable status code if processed by a service). When a service input is determined by a firewall to be desirable, the firewall may push the service input through to the input processing service for normal processing. When a service input is determined by the firewall to be undesirable, the firewall may block or drop the service input before it reaches the input processing service and/or server. This may be used to prevent the service input, which is likely to be undesirable, from touching a server that hosts the input processing service (e.g., preventing a crash).

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