DATA UNBLOCKING IN APPLICATION PLATFORMS
    12.
    发明公开

    公开(公告)号:US20230267111A1

    公开(公告)日:2023-08-24

    申请号:US17679972

    申请日:2022-02-24

    Applicant: SAP SE

    Abstract: Systems, methods, and computer-readable media are disclosed for data unblocking in application platforms. An application platform may comprise a plurality of systems. A system may store data having a residence period. Upon expiration of the residence period, the data may be blocked from further processing. Data which is blocked may need to then be unblocked. Systems may be leading systems or dependent systems. Data unblocking may be triggered from the leading system to the dependent systems. At runtime, the dependent system may receive a trust token which may be used to verify a calling system as the leading system. If a data unblocking request is called from a dependent system, data unblocking may be prevented.

    RETRIEVAL OF UNSTRUCTURED DATA IN DPP INFORMATION ACCESS

    公开(公告)号:US20230054316A1

    公开(公告)日:2023-02-23

    申请号:US17404451

    申请日:2021-08-17

    Applicant: SAP SE

    Abstract: Systems, methods, and computer-readable media are disclosed for the centralized retrieval of personal data about a data subject across a plurality of applications. The data subject may request the retrieval of personal data from a company. To retrieve the personal data, a data model may be created for each application having personal data about the data subject. Each application may store personal data in the form of attachments. The data model may be in tabular form and store virtual representations of the attachments. Metadata for the attachments may be retrieved using the virtual representations of the attachments. The attachment metadata may then be used to retrieve the attachments. The attachments may then be provided to the data subject for download. The personal data may be provided to the data subject in both machine-readable and human-readable form to comply with data privacy regulations.

    Anonymized data storage and retrieval

    公开(公告)号:US11048820B2

    公开(公告)日:2021-06-29

    申请号:US15656858

    申请日:2017-07-21

    Applicant: SAP SE

    Inventor: Naved Ahmed

    Abstract: Systems and methods for applying k-anonymity to data from a database are provided. An initial extraction of data from a database is performed. Initial anonymized data is produced based on the extracted data and a configuration of quasi-identifiers. An actual k-anonymity level is calculated based on the initial anonymized data. The actual k-anonymity level is compared to a desired k-anonymity level. The configuration of quasi-identifiers is adjusted based on the comparison. The calculating, comparing, and adjusting are iteratively repeated until the actual k-anonymity level equals the desired k-anonymity level or the adjusted configuration of quasi-identifiers has reached a limit. Final anonymized data is produced based on the adjusted configuration of quasi-identifiers. A subsequent extraction of data from the database is performed. Subsequent anonymized data is produced based on the extracted subsequent data and the adjusted configuration of quasi-identifiers. The actual k-anonymity level is calculated based on the subsequent anonymized data.

    Anonymized Data Storage and Retrieval
    15.
    发明申请

    公开(公告)号:US20190026490A1

    公开(公告)日:2019-01-24

    申请号:US15656858

    申请日:2017-07-21

    Applicant: SAP SE

    Inventor: Naved Ahmed

    Abstract: Systems and methods for applying k-anonymity to data from a database are provided. An initial extraction of data from a database is performed. Initial anonymized data is produced based on the extracted data and a configuration of quasi-identifiers. An actual k-anonymity level is calculated based on the initial anonymized data. The actual k-anonymity level is compared to a desired k-anonymity level. The configuration of quasi-identifiers is adjusted based on the comparison. The calculating, comparing, and adjusting are iteratively repeated until the actual k-anonymity level equals the desired k-anonymity level or the adjusted configuration of quasi-identifiers has reached a limit. Final anonymized data is produced based on the adjusted configuration of quasi-identifiers. A subsequent extraction of data from the database is performed. Subsequent anonymized data is produced based on the extracted subsequent data and the adjusted configuration of quasi-identifiers. The actual k-anonymity level is calculated based on the subsequent anonymized data.

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