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    REAL-TIME PREDICTIONS BASED ON MACHINE LEARNING MODELS
    1.
    发明申请
    REAL-TIME PREDICTIONS BASED ON MACHINE LEARNING MODELS 有权

    公开(公告)号：US20210241179A1

    公开(公告)日：2021-08-05

    申请号：US16777686

    申请日：2020-01-30

    Applicant: salesforce.com, inc.

    Inventor： Rakesh Ganapathi Karanth ,  Arun Kumar Jagota ,  Kaushal Bansal ,  Amrita Dasgupta

    IPC: G06N20/20 ,  G06N7/00

    Abstract: An online system performs predictions for real-time tasks and near real-time tasks that need to be performed by a deadline. A client device receives a real-time machine learning based model associated with a measure of accuracy. If the client device determines that a task can be performed using predictions having less than the specified measure of accuracy, the client device uses the real-time machine learning based model. If the client device determines that a higher level of accuracy of results is required, the client device sends a request to an online system. The online system provides a prediction along with a string representing a rationale for the prediction.

    Incrementally validating security policy code using information from an infrastructure as code repository
    2.
    发明授权
    Incrementally validating security policy code using information from an infrastructure as code repository 有权

    公开(公告)号：US11977476B2

    公开(公告)日：2024-05-07

    申请号：US17587896

    申请日：2022-01-28

    Applicant: salesforce.com, inc.

    Inventor： Kaushal Bansal ,  Prabhat Singh ,  Selim Ciraci

    IPC: G06F11/36 ,  H04L9/40

    CPC classification number: G06F11/368 ,  G06F11/3664 ,  G06F11/3692 ,  H04L63/20

    Abstract: In an example, an apparatus may include a validation module configured to identify a security policy update from a security as code repository, wherein the identified security policy update is a candidate for deployment to a production environment having a plurality of attributes defined by an infrastructure as code repository; identify, from the plurality of attributes and using the infrastructure as code repository, individual attributes that correspond to the identified security policy update, wherein the identified individual attributes are identical to a subset of the plurality of attributes; generate a test environment based on the identified individual attributes; following deployment of the identified security policy update to the test environment, check for security exceptions or availability exceptions using the test environment; and output validation results based on a result of the checking.

    Linking records between datasets to augment query results
    4.
    发明授权
    Linking records between datasets to augment query results 有权

    公开(公告)号：US10810233B2

    公开(公告)日：2020-10-20

    申请号：US15844311

    申请日：2017-12-15

    Applicant: salesforce.com, inc.

    Inventor： Kaushal Bansal ,  Venkata Muralidhar Tejomurtula ,  Azeem Feroz ,  Dmytro Kashyn ,  Dmytro Kudriavtsev

    IPC: G06F7/02 ,  G06F16/00 ,  G06F16/28 ,  G06F16/23 ,  G06F16/9535 ,  G06F16/25 ,  G06F16/2458

    Abstract: A method for linking records from different datasets based on record similarities is described. The method includes ingesting a first dataset, including a first set of records with a first set of fields, wherein the first dataset is associated with a first vendor and a first type of data, and a second dataset, including a second set of records with a second set of fields, wherein the second dataset is associated with a second vendor and a second type of data; determining that a first record from the first set of records is similar to a second record from the second set of records based on similarities between fields in the first and second set of fields; and linking the first and second records in response to determining that the similarity, wherein the first and second vendors are different and/or the first and second types of data are different.

    STATELESS MUTUAL AUTHENTICATION BETWEEN SERVICES
    5.
    发明申请
    STATELESS MUTUAL AUTHENTICATION BETWEEN SERVICES 有权

    公开(公告)号：US20210328807A1

    公开(公告)日：2021-10-21

    申请号：US16849275

    申请日：2020-04-15

    Applicant: salesforce.com, inc.

    Inventor： Kaushal Bansal ,  Tejas Badadare ,  Jonathan Dean Smith

    IPC: H04L9/32 ,  H04L29/06 ,  H04L29/08

    Abstract: A server computing system generates a universally unique identifier (UUID) associated with a first application, the UUID to be encrypted using a private key associated with the first application to generate a first digital signature. The server computing system generates a first session key associated with the first application, the first digital signature to be encrypted using the first session key to generate a first encrypted digital signature. The server computing system encrypts the first session key using a public key associated with a second application to generate a first encrypted session key, wherein the first application and the second application are deployed with the PaaS associated with the server computing system. The server computing system transmits the UUID, the first encrypted digital signature, and the first encrypted session key to the second application using hypertext transfer protocol (HTTP) to enable the second application to authenticate the first application.

    Real-time predictions based on machine learning models
    6.
    发明授权
    Real-time predictions based on machine learning models 有权

    公开(公告)号：US11651291B2

    公开(公告)日：2023-05-16

    申请号：US16777686

    申请日：2020-01-30

    Applicant: salesforce.com, inc.

    Inventor： Rakesh Ganapathi Karanth ,  Arun Kumar Jagota ,  Kaushal Bansal ,  Amrita Dasgupta

    IPC: G06N20/20 ,  G06N7/00

    CPC classification number: G06N20/20 ,  G06N7/005

    Abstract: An online system performs predictions for real-time tasks and near real-time tasks that need to be performed by a deadline. A client device receives a real-time machine learning based model associated with a measure of accuracy. If the client device determines that a task can be performed using predictions having less than the specified measure of accuracy, the client device uses the real-time machine learning based model. If the client device determines that a higher level of accuracy of results is required, the client device sends a request to an online system. The online system provides a prediction along with a string representing a rationale for the prediction.

    Stateless mutual authentication between services
    8.
    发明授权
    Stateless mutual authentication between services 有权

    公开(公告)号：US11552802B2

    公开(公告)日：2023-01-10

    申请号：US16849275

    申请日：2020-04-15

    Applicant: salesforce.com, inc.

    Inventor： Kaushal Bansal ,  Tejas Badadare ,  Jonathan Dean Smith

    IPC: H04L29/06 ,  H04L9/32 ,  H04L67/02 ,  H04L9/40

    Abstract: A server computing system generates a universally unique identifier (UUID) associated with a first application, the UUID to be encrypted using a private key associated with the first application to generate a first digital signature. The server computing system generates a first session key associated with the first application, the first digital signature to be encrypted using the first session key to generate a first encrypted digital signature. The server computing system encrypts the first session key using a public key associated with a second application to generate a first encrypted session key, wherein the first application and the second application are deployed with the PaaS associated with the server computing system. The server computing system transmits the UUID, the first encrypted digital signature, and the first encrypted session key to the second application using hypertext transfer protocol (HTTP) to enable the second application to authenticate the first application.

    DETERMINING RATIONALE FOR A PREDICTION OF A MACHINE LEARNING BASED MODEL
    9.
    发明申请
    DETERMINING RATIONALE FOR A PREDICTION OF A MACHINE LEARNING BASED MODEL 有权

    公开(公告)号：US20210241047A1

    公开(公告)日：2021-08-05

    申请号：US16778925

    申请日：2020-01-31

    Applicant: salesforce.com, inc.

    Inventor： Rakesh Ganapathi Karanth ,  Arun Kumar Jagota ,  Kaushal Bansal ,  Amrita Dasgupta

    IPC: G06K9/62 ,  G06N5/04 ,  G06N20/00

    Abstract: An online system performs predictions for real-time tasks and near real-time tasks that need to be performed by a deadline. A client device receives a real-time machine learning based model associated with a measure of accuracy. If the client device determines that a task can be performed using predictions having less than the specified measure of accuracy, the client device uses the real-time machine learning based model. If the client device determines that a higher level of accuracy of results is required, the client device sends a request to an online system. The online system provides a prediction along with a string representing a rationale for the prediction.

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