Patents by Inventor Pedro Barbas
Pedro Barbas has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11468192Abstract: A computer-implemented method, computer program product and system for identifying pseudonymized data within data sources. One or more data repositories within one or more of the data sources are selected. One or more privacy data models are provided, where each of the privacy data models includes pattern(s) and/or parameter(s). One or more of the one or more privacy data models are selected. Data identification information is generated, where the data identification information indicates a presence or absence of pseudonymized data and of non-pseudonymized data within the one or more of the data sources. The data identification information is generated utilizing the pattern(s) and/or the parameter(s) to determine pseudonymized data.Type: GrantFiled: March 25, 2020Date of Patent: October 11, 2022Inventors: Pedro Barbas, Austin Clifford, Konrad Emanowicz, Patrick G. O'Sullivan
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Patent number: 11036684Abstract: Disclosed is an approach comprising a column partitioned into a plurality of partitions including an empty partition and a plurality of filled partitions each comprising data entries associated with a set of parameters having parameter values, the data entries compressed in accordance with a compression dictionary. The approach comprises receiving forecasted parameter values for an expected set of data entries to be stored in an empty partition; predicting a recurrence frequency of the data entries in the expected set using the forecasted parameter values by evaluating the respective compression dictionaries of the filled partitions with a machine learning algorithm; generating a predictive compression dictionary for the expected set of data entries based on the predicted recurrence frequency of the data entries in the expected set; receiving the expected set of data entries; and compressing at least part of the received expected set of data entries using the predictive compression dictionary.Type: GrantFiled: November 29, 2018Date of Patent: June 15, 2021Assignee: International Business Machines CorporationInventors: Sami Abed, Pedro Barbas, Austin Clifford, Konrad Emanowicz
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Patent number: 10747903Abstract: A computer-implemented method, computer program product and system for identifying pseudonymized data within data sources. One or more data repositories within one or more of the data sources are selected. One or more privacy data models are provided, where each of the privacy data models includes pattern(s) and/or parameter(s). One or more of the one or more privacy data models are selected. Data identification information is generated, where the data identification information indicates a presence or absence of pseudonymized data and of non-pseudonymized data within the one or more of the data sources. The data identification information is generated utilizing the pattern(s) and/or the parameter(s) to determine pseudonymized data.Type: GrantFiled: April 25, 2019Date of Patent: August 18, 2020Assignee: International Business Machines CorporationInventors: Pedro Barbas, Austin Clifford, Konrad Emanowicz, Patrick G. O'Sullivan
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Publication number: 20200226289Abstract: A computer-implemented method, computer program product and system for identifying pseudonymized data within data sources. One or more data repositories within one or more of the data sources are selected. One or more privacy data models are provided, where each of the privacy data models includes pattern(s) and/or parameter(s). One or more of the one or more privacy data models are selected. Data identification information is generated, where the data identification information indicates a presence or absence of pseudonymized data and of non-pseudonymized data within the one or more of the data sources. The data identification information is generated utilizing the pattern(s) and/or the parameter(s) to determine pseudonymized data.Type: ApplicationFiled: March 25, 2020Publication date: July 16, 2020Inventors: Pedro Barbas, Austin Clifford, Konrad Emanowicz, Patrick G. O'Sullivan
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Patent number: 10657287Abstract: A computer-implemented method, computer program product and system for identifying pseudonymized data within data sources. One or more data repositories within one or more of the data sources are selected. One or more privacy data models are provided, where each of the privacy data models includes pattern(s) and/or parameter(s). One or more of the one or more privacy data models are selected. Data identification information is generated, where the data identification information indicates a presence or absence of pseudonymized data and of non-pseudonymized data within the one or more of the data sources. The data identification information is generated utilizing the pattern(s) and/or the parameter(s) to determine pseudonymized data.Type: GrantFiled: November 1, 2017Date of Patent: May 19, 2020Assignee: International Business Machines CorporationInventors: Pedro Barbas, Austin Clifford, Konrad Emanowicz, Patrick G. O'Sullivan
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Publication number: 20190251292Abstract: A computer-implemented method, computer program product and system for identifying pseudonymized data within data sources. One or more data repositories within one or more of the data sources are selected. One or more privacy data models are provided, where each of the privacy data models includes pattern(s) and/or parameter(s). One or more of the one or more privacy data models are selected. Data identification information is generated, where the data identification information indicates a presence or absence of pseudonymized data and of non-pseudonymized data within the one or more of the data sources. The data identification information is generated utilizing the pattern(s) and/or the parameter(s) to determine pseudonymized data.Type: ApplicationFiled: April 25, 2019Publication date: August 15, 2019Inventors: Pedro Barbas, Austin Clifford, Konrad Emanowicz, Patrick G. O'Sullivan
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Publication number: 20190130132Abstract: A computer-implemented method, computer program product and system for identifying pseudonymized data within data sources. One or more data repositories within one or more of the data sources are selected. One or more privacy data models are provided, where each of the privacy data models includes pattern(s) and/or parameter(s). One or more of the one or more privacy data models are selected. Data identification information is generated, where the data identification information indicates a presence or absence of pseudonymized data and of non-pseudonymized data within the one or more of the data sources. The data identification information is generated utilizing the pattern(s) and/or the parameter(s) to determine pseudonymized data.Type: ApplicationFiled: November 1, 2017Publication date: May 2, 2019Inventors: Pedro Barbas, Austin Clifford, Konrad Emanowicz, Patrick G. O'Sullivan
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Publication number: 20190095461Abstract: Disclosed is an approach comprising a column partitioned into a plurality of partitions including an empty partition and a plurality of filled partitions each comprising data entries associated with a set of parameters having parameter values, the data entries compressed in accordance with a compression dictionary. The approach comprises receiving forecasted parameter values for an expected set of data entries to be stored in an empty partition; predicting a recurrence frequency of the data entries in the expected set using the forecasted parameter values by evaluating the respective compression dictionaries of the filled partitions with a machine learning algorithm; generating a predictive compression dictionary for the expected set of data entries based on the predicted recurrence frequency of the data entries in the expected set; receiving the expected set of data entries; and compressing at least part of the received expected set of data entries using the predictive compression dictionary.Type: ApplicationFiled: November 29, 2018Publication date: March 28, 2019Inventors: Sami Abed, Pedro Barbas, Austin Clifford, Konrad Emanowicz
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Patent number: 9135315Abstract: Aspects include data masking in database operations including intercepting a database query and identifying masked data in the query. The masked data in the query is unmasked by substituting the masked data with equivalent real values. The unmasked query is sent to the database engine, and a result provided by the database engine in response to the unmasked query is intercepted. The values in the result that correspond to sensitive information are identified. The result is masked by substituting the values in the result corresponding to sensitive information with masked equivalents. The masked result is returned to a user.Type: GrantFiled: February 26, 2013Date of Patent: September 15, 2015Assignee: Internatonal Business Machines CorporationInventors: Pedro Barbas, Austin Clifford, Gareth Jenkins, Brian McKeown
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Publication number: 20130282697Abstract: Aspects include data masking in database operations including intercepting a database query and identifying masked data in the query. The masked data in the query is unmasked by substituting the masked data with equivalent real values. The unmasked query is sent to the database engine, and a result provided by the database engine in response to the unmasked query is intercepted. The values in the result that correspond to sensitive information are identified. The result is masked by substituting the values in the result corresponding to sensitive information with masked equivalents. The masked result is returned to a user.Type: ApplicationFiled: February 26, 2013Publication date: October 24, 2013Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Pedro Barbas, Austin Clifford, Gareth Jenkins, Brian McKeown