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    SYSTEMS AND METHODS FOR AUTOMATICALLY BLOCKING THE USE OF TRACKING TOOLS
    1.
    发明公开
    SYSTEMS AND METHODS FOR AUTOMATICALLY BLOCKING THE USE OF TRACKING TOOLS 审中-公开

    公开(公告)号：US20240195835A1

    公开(公告)日：2024-06-13

    申请号：US18586958

    申请日：2024-02-26

    申请人： OneTrust, LLC

    发明人： Jonathan Blake Brannon ,  Patrick Whitney ,  Sharath Chandra Chavva ,  Jeffrey Baucom

    IPC分类号： H04L9/40

    CPC分类号： H04L63/1475 ,  H04L63/1416

    摘要： Embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for permitting or blocking tracking tools used through webpages. In particular embodiments, the method involves: scanning a webpage to identify a tracking tool configured for processing personal data; determining a data destination location that is associated with the tracking tool; and generating program code configured to: determine a location associated with a user who is associated with a rendering of the webpage; determine a prohibited data destination location based on the location associated with the user; determine that the data destination location associated with the tracking tool is not the prohibited data destination location; and responsive to the data destination location associated with the tracking tool not being the prohibited data destination location, permit the tracking tool to execute.

    PROCESSING AND PUBLISHING SCANNED DATA FOR DETECTING ENTITIES IN A SET OF DOMAINS VIA A PARALLEL PIPELINE
    2.
    发明公开
    PROCESSING AND PUBLISHING SCANNED DATA FOR DETECTING ENTITIES IN A SET OF DOMAINS VIA A PARALLEL PIPELINE 审中-公开

    公开(公告)号：US20240143674A1

    公开(公告)日：2024-05-02

    申请号：US18476185

    申请日：2023-09-27

    申请人： OneTrust LLC

    发明人： Raju Bokade ,  Ravi Kalasapur ,  Mithun Babu ,  Austin Proctor

    IPC分类号： G06F16/951 ,  G06F9/50

    CPC分类号： G06F16/951 ,  G06F9/5027

    摘要： Methods, systems, and non-transitory computer readable storage media are disclosed for processing data for a subset of domains in parallel with publishing data to a tenant database for another subset of domains within a shared infrastructure. Specifically, the disclosed system assigns one or more partitions of an intermediate shared processing queue to a set of domains indicated by a scan request from a client device. The disclosed system extracts data from a subset of domains of the set of domains via the one or more partitions and publishes scan results of the subset of domains to the tenant database. Furthermore, the disclosed system extracts, in parallel with publishing the data of the subset of domains, additional data of an additional subset of domains via the one or more partitions of the intermediate shared processing queue.

    Systems and methods for automatically blocking the use of tracking tools
    3.
    发明授权
    Systems and methods for automatically blocking the use of tracking tools 有权

    公开(公告)号：US11968229B2

    公开(公告)日：2024-04-23

    申请号：US17942242

    申请日：2022-09-12

    申请人： OneTrust, LLC

    发明人： Jonathan Blake Brannon ,  Patrick Whitney ,  Sharath Chandra Chavva ,  Jeffrey Baucom

    IPC分类号： H04L9/40

    CPC分类号： H04L63/1475 ,  H04L63/1416

    摘要： Embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for permitting or blocking tracking tools used through webpages. In particular embodiments, the method involves: scanning a webpage to identify a tracking tool configured for processing personal data; determining a data destination location that is associated with the tracking tool; and generating program code configured to: determine a location associated with a user who is associated with a rendering of the webpage; determine a prohibited data destination location based on the location associated with the user; determine that the data destination location associated with the tracking tool is not the prohibited data destination location; and responsive to the data destination location associated with the tracking tool not being the prohibited data destination location, permit the tracking tool to execute.

    SYSTEMS AND METHODS FOR MITIGATING RISKS OF THIRD-PARTY COMPUTING SYSTEM FUNCTIONALITY INTEGRATION INTO A FIRST-PARTY COMPUTING SYSTEM
    4.
    发明公开
    SYSTEMS AND METHODS FOR MITIGATING RISKS OF THIRD-PARTY COMPUTING SYSTEM FUNCTIONALITY INTEGRATION INTO A FIRST-PARTY COMPUTING SYSTEM 审中-公开

    公开(公告)号：US20240098109A1

    公开(公告)日：2024-03-21

    申请号：US18275910

    申请日：2022-02-10

    申请人： OneTrust, LLC

    发明人： Subramanian Viswanathan ,  Milap Shah

    IPC分类号： H04L9/40 ,  G06F21/60

    CPC分类号： H04L63/1433 ,  G06F21/60

    摘要： In general, various aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for integrating third party computing system functionality into a first party computing system by providing a risk management and mitigation computing system configured to analyze a risk of integrating the functionality provided by the third party computing system and facilitating implementation of one or more data-related controls that include performing computer-specific operations to mitigate and/or eliminate the identified risks. For example, the risk management and mitigation computing system can access risk data in tenant computing systems to determine a risk score related to the integration of the third party computing system functionality based on risks determined during prior integrations of the third party computing system functionality by other tenant computing systems. The risk management and mitigation computing system can generate a recommended control when integrating the third party computing system functionality.

    MANAGING THE DEVELOPMENT AND USAGE OF MACHINE-LEARNING MODELS AND DATASETS VIA COMMON DATA OBJECTS
    5.
    发明公开
    MANAGING THE DEVELOPMENT AND USAGE OF MACHINE-LEARNING MODELS AND DATASETS VIA COMMON DATA OBJECTS 审中-公开

    公开(公告)号：US20230376852A1

    公开(公告)日：2023-11-23

    申请号：US18319301

    申请日：2023-05-17

    申请人： OneTrust LLC

    发明人： Shane Wiggins ,  Kevin Jones

    IPC分类号： G06N20/00

    CPC分类号： G06N20/00

    摘要： Methods, systems, and non-transitory computer readable storage media are disclosed for managing implementation of machine-learning models within computing environments according to system requirements frameworks via common data objects. The disclosed system generates a common data object to represent an implementation of a machine-learning model with a data process. For example, the disclosed system determines attribute values of the common data object according to data objects representing the machine-learning model and related datasets. Furthermore, the disclosed system utilizes the common data object to validate the machine-learning model according to a digital representation of a system requirements framework that includes usage requirements for machine-learning models to store, process, transmit, or otherwise handle specific data types in specific ways for the one or more data processes within a computing environment. The disclosed systems also perform operations to implement, suspend, or otherwise modify the machine-learning model or datasets based on the validation.

    DATA PROCESSING SYSTEMS AND METHODS FOR AUTOMATICALLY DETECTING TARGET DATA TRANSFERS AND TARGET DATA PROCESSING
    7.
    发明公开
    DATA PROCESSING SYSTEMS AND METHODS FOR AUTOMATICALLY DETECTING TARGET DATA TRANSFERS AND TARGET DATA PROCESSING 审中-公开

    公开(公告)号：US20230334158A1

    公开(公告)日：2023-10-19

    申请号：US18027217

    申请日：2021-09-21

    申请人： OneTrust, LLC

    发明人： Jonathan Blake Brannon ,  Patrick Whitney

    IPC分类号： G06F21/57 ,  G06F21/55

    CPC分类号： G06F21/577 ,  G06F21/55

    摘要： Aspects of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for protection of system software, or data from destruction, unauthorized modification, and/or unauthorized disclosure securing by, for example, detecting the transfer and/or processing of target data. Accordingly, a method is provided that involves: scanning a software application to identify functionality configured for processing target data; identifying fields associated with the functionality; identifying metadata associated with a field; generating, from the metadata, an identification of a type of data associated with the field; determining a location based on the processing of the target data by the functionality; determining a risk associated with the functionality processing the target data based on the location and the type of data; determining that the risk satisfies a threshold level of risk; and in response, causing an action to be performed to mitigate the risk.

    MAPPING ENTITIES IN UNSTRUCTURED TEXT DOCUMENTS VIA ENTITY CORRECTION AND ENTITY RESOLUTION
    9.
    发明公开
    MAPPING ENTITIES IN UNSTRUCTURED TEXT DOCUMENTS VIA ENTITY CORRECTION AND ENTITY RESOLUTION 审中-公开

    公开(公告)号：US20230267274A1

    公开(公告)日：2023-08-24

    申请号：US17813384

    申请日：2022-07-19

    申请人： OneTrust LLC

    发明人： Madan Avadhani ,  Siddhartha Kille

    IPC分类号： G06F40/284 ,  G06F40/295 ,  G06V30/32 ,  G06K9/62

    CPC分类号： G06F40/284 ,  G06F40/295 ,  G06V30/32 ,  G06K9/6215

    摘要： Methods, systems, and non-transitory computer readable storage media are disclosed for correcting entity detection errors with entity correction and resolution in optical character recognition for digitization of physical documents. Specifically, the disclosed system utilizes named entity recognition to extract entities from character strings (e.g., words) in a digital text document. The disclosed system also tokenizes the character strings in the digital text document based on attributes of the character strings. Furthermore, the disclosed system compares the extracted entities and tokenized character strings to determine similarity metrics between the extracted entities and tokenized character strings. The disclosed system also compares extracted entities to character strings including special/numerical characters to determine similarity metrics indicating correlation probabilities between entities and character strings. The disclosed systems generate mappings between the tokens and entities based on the similarity metrics to resolve entities to likely corresponding character strings while correcting for errors during entity extraction.