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    Satellite service for machine authentication in hybrid environments
    124.
    发明授权
    Satellite service for machine authentication in hybrid environments 有权

    公开(公告)号：US11647020B2

    公开(公告)日：2023-05-09

    申请号：US16825437

    申请日：2020-03-20

    Applicant: INTUIT INC.

    Inventor： Gleb Keselman

    IPC: H04L9/40 ,  H04L9/32

    CPC classification number: H04L63/0853 ,  H04L9/3247 ,  H04L63/083 ,  H04L63/10

    Abstract: Certain aspects of the present disclosure provide techniques for access control. Embodiments include receiving, by a satellite component of an access control system, a request from a computing device to verify an identity of the computing device, wherein the request comprises one or more characteristics of the computing device. Embodiments include verifying, by the satellite component, that the one or more characteristics of the computing device are valid, the verifying comprising one or more interactions with a management entity related to the computing device. Embodiments include generating, by the satellite component, a signed document that is trusted by a control component of the access control system. Embodiments include providing, by the satellite component, the signed document to the computing device for use in requesting credentials from the control component to access a secure resource.

    Ensemble of machine learning models for real-time predictions in expert electronic chats
    125.
    发明授权
    Ensemble of machine learning models for real-time predictions in expert electronic chats 有权

    公开(公告)号：US11646014B1

    公开(公告)日：2023-05-09

    申请号：US17814759

    申请日：2022-07-25

    Applicant: INTUIT INC.

    Inventor： Shrutendra Harsola ,  Sourav Prosad ,  Viswa Datha Polavarapu

    IPC: G10L15/16 ,  G10L15/197 ,  G06N3/045 ,  G06N3/047

    CPC classification number: G10L15/16 ,  G06N3/045 ,  G06N3/047 ,  G10L15/197

    Abstract: An ensemble of machine learning models used for real-time prediction of text for an electronic chat with an expert user. A global machine learning model, e.g., a transformer model, trained with domain specific knowledge makes a domain specific generalized prediction. Another machine learning model, e.g., an n-gram model, learns the specific style of the expert user as the expert user types to generate more natural, more expert user specific text. If specific words cannot be predicted with a desired probability level, another word level machine learning model, e.g., a word completion model, completes the words as the characters are being typed. The ensemble therefore produces real-time, natural, and accurate text that is provided to the expert user. Continuous feedback of the acceptance/rejection of predictions by the expert is used to fine tune one or more machine learning models of the ensemble in real time.

    Capturing variable dependencies using a variable agnostic object
    127.
    发明授权
    Capturing variable dependencies using a variable agnostic object 有权

    公开(公告)号：US11645056B2

    公开(公告)日：2023-05-09

    申请号：US17376526

    申请日：2021-07-15

    Applicant: Intuit Inc.

    Inventor： Samarinder Singh Thind ,  Rajat Khare ,  Neelam Singh ,  Suresh Krishna Devanathan ,  Deepak Radhakrishna

    IPC: G06F8/41 ,  H04L67/00 ,  G06F8/20

    CPC classification number: G06F8/433 ,  G06F8/24 ,  H04L67/34

    Abstract: Capturing dependencies between variables using a variable agnostic object is disclosed. A system is configured to obtain an indication of a first dependency of a first variable to a second variable via a programming interface and depict the first dependency, the first variable, and the second variable in a first instance of a variable agnostic object in a source code. The system is also configured to obtain an indication of a second dependency of a third variable to a fourth variable via the programming interface and depict the second dependency, the third variable, and the fourth variable in a second instance of the variable agnostic object in the source code. The system is also configured to compile the source code to generate a computer-executable program capturing the first dependency and the second dependency based on the first instance and the second instance of the variable agnostic object.

    GRADIENT BASED ANOMALY DETECTION SYSTEM FOR TIME SERIES FEATURES
    128.
    发明申请
    GRADIENT BASED ANOMALY DETECTION SYSTEM FOR TIME SERIES FEATURES 有权

    公开(公告)号：US20230137553A1

    公开(公告)日：2023-05-04

    申请号：US17512887

    申请日：2021-10-28

    Applicant: Intuit Inc.

    Inventor： Aviv BEN ARIE ,  Or BASSON ,  Nitzan BAVLY ,  Yair HORESH

    IPC: G06N20/00

    Abstract: Systems and methods for identifying suspected anomalies in time series data are disclosed. An example method may receiving time series data for at least one quantity, the time series data including values of the at least one quantity at each of a plurality of times, determining a list of gradients for the time series data, each gradient in the list of gradients based on two or more values of the time series data separated by a specified number of values of the time series data, deriving a plurality of statistics based on the determined list of gradients, and performing a supervised machine learning process based on the derived plurality of statistics to generate a trained machine learning model for identifying one or more suspected anomalies in the time series data.

    MINIMIZING RISKS POSED TO ONLINE SERVICES
    129.
    发明申请
    MINIMIZING RISKS POSED TO ONLINE SERVICES 有权

    公开(公告)号：US20230134689A1

    公开(公告)日：2023-05-04

    申请号：US17515327

    申请日：2021-10-29

    Applicant: Intuit Inc.

    Inventor： Nghiem LE ,  Leandro ALVES ,  Nikolas TERANI ,  Eugene BENDERSKY ,  Taylor CRESSY

    IPC: G06Q20/40 ,  G06Q20/24

    Abstract: A system receives a request for payment of a transaction between a vendor and a consumer, and sends a first request to a database associated with the online service for historical transactions and personal attributes of the vendor concurrently with sending a second request to a number of third-party services for credit information and personal attributes of the consumer. The system receives information responsive to the first and second requests from the database and the third-party services, respectively, and obtains a risk score for the transaction based on an application of one or more risk assessment rules to the received information by a machine learning model trained with at least the historical transactions and the personal attributes of the vendor. In some aspects, the system determines whether to advance funds to the vendor, prior to requesting payment from a consumer account, based at least in part on the risk score.

    METRICS-BASED ON-DEMAND ANOMALY DETECTION
    130.
    发明申请
    METRICS-BASED ON-DEMAND ANOMALY DETECTION 有权

    公开(公告)号：US20230132670A1

    公开(公告)日：2023-05-04

    申请号：US17515377

    申请日：2021-10-29

    Applicant: Intuit Inc.

    Inventor： Amit Shriram Kalamkar ,  Vigith Maurice ,  Avik Basu

    IPC: G06N20/00

    Abstract: A method for metrics-based anomaly detection involves receiving an anomaly analysis request for an asset and obtaining metrics associated with the asset. Each of the metrics includes time series data. The method further involves detecting that one of the metrics is a counter. The detection involves seasonally differencing the metric, obtaining a regression line by performing a linear regression on the metric, and determining that an angle of the regression line exceeds a predetermined threshold angle. The method also involves training models for the metrics, the training including training a counter-specific model for the metric that is a counter. The method further involves determining, using the models after the training, at least one metric that is anomalous.

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