Patents by Inventor Martin Scaiano
Martin Scaiano 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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Publication number: 20230409750Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.Type: ApplicationFiled: September 1, 2023Publication date: December 21, 2023Inventors: Sean Rose, Weilong Song, Martin Scaiano
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Patent number: 11748517Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.Type: GrantFiled: April 27, 2022Date of Patent: September 5, 2023Assignee: Privacy Analytics Inc.Inventors: Sean Rose, Weilong Song, Martin Scaiano
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Publication number: 20220253559Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.Type: ApplicationFiled: April 27, 2022Publication date: August 11, 2022Inventors: Sean Rose, Weilong Song, Martin Scaiano
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Patent number: 11334685Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.Type: GrantFiled: February 26, 2020Date of Patent: May 17, 2022Assignee: PRIVACY ANALYTICS INC.Inventors: Sean Rose, Weilong Song, Martin Scaiano
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Patent number: 10803201Abstract: System and method to produce an anonymized electronic data product having an individually-determined threshold of re-identification risk, and adjusting re-identification risk measurement parameters based on individual characteristics such as geographic location, in order to provide an anonymized electronic data product having a sensitivity-based reduced risk of re-identification.Type: GrantFiled: February 26, 2018Date of Patent: October 13, 2020Assignee: PRIVACY ANALYTICS INC.Inventors: Hazel Joyce Nicholls, Andrew Richard Baker, Yasser Jafer, Martin Scaiano
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Publication number: 20200193060Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.Type: ApplicationFiled: February 26, 2020Publication date: June 18, 2020Inventors: Sean Rose, Weilong Song, Martin Scaiano
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Patent number: 10685138Abstract: There is provided a system and method executed by a processor for estimating re-identification risk of a single individual in a dataset. The individual, subject or patient is described by a data subject profile such as a record in the dataset. A population distribution is retrieved from a storage device, the population distribution is determined by one or more quasi-identifying fields identified in the data subject profile. An information score is then assigned to each quasi-identifying (QI) value of the one or more quasi-identifying fields associated with the data subject profile. The assigned information scores of the quasi-identifying values for the data subject profile are aggregated into an aggregated information value. An anonymity value is then calculated from the aggregated information value and a size of a population associated with the dataset. A re-identification metric for the individual from the anonymity value is then calculated.Type: GrantFiled: April 1, 2016Date of Patent: June 16, 2020Assignee: PRIVACY ANALYTICS INC.Inventors: Martin Scaiano, Stephen Korte, Andrew Baker, Geoffrey Green, Khaled El Emam, Luk Arbuckle
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Patent number: 10586074Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.Type: GrantFiled: April 30, 2019Date of Patent: March 10, 2020Assignee: PRIVACY ANALYTICS INC.Inventors: Sean Rose, Weilong Song, Martin Scaiano
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Patent number: 10423803Abstract: System and method to produce an anonymized cohort, members of the cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits to request in an anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and calculating an anonymity histogram of the dataset. For each patient record within the dataset, the method anonymizes the dataset by calculating using a threshold selector whether a predetermined patient profile within the dataset should be perturbed, calculating using a value selector whether a value within the indicated patient profile should be perturbed, and suppressing an indicated value within the indicated patient profile. The anonymized dataset then is returned.Type: GrantFiled: December 23, 2016Date of Patent: September 24, 2019Assignee: PRIVACY ANALYTICS INC.Inventors: Martin Scaiano, Andrew Baker, Stephen Korte
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Patent number: 10395059Abstract: A computer-implemented system and method to reduce re-identification risk of a data set. The method includes the steps of retrieving, via a database-facing communication channel, a data set from a database communicatively coupled to the processor, the data set selected to include patient medical records that meet a predetermined criteria; identifying, by a processor coupled to a memory, direct identifiers in the data set; identifying, by the processor, quasi-identifiers in the data set; calculating, by the processor, a first probability of re-identification from the direct identifiers; calculating, by the processor, a second probability of re-identification from the quasi-direct identifiers; perturbing, by the processor, the data set if one of the first probability or second probability exceeds a respective predetermined threshold, to produce a perturbed data set; and providing, via a user-facing communication channel, the perturbed data set to the requestor.Type: GrantFiled: March 7, 2017Date of Patent: August 27, 2019Assignee: PRIVACY ANALYTICS INC.Inventors: Martin Scaiano, Grant Middleton, Varada Kolhatkar, Khaled El Emam
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Publication number: 20190258826Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.Type: ApplicationFiled: April 30, 2019Publication date: August 22, 2019Inventors: Sean Rose, Weilong Song, Martin Scaiano
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Patent number: 10380381Abstract: System and method to predict risk of re-identification of a cohort if the cohort is anonymized using a de-identification strategy. An input anonymity histogram and de-identification strategy is used to predict the anonymity histogram that would result from applying the de-identification strategy to the dataset. System embodiments compute a risk of re-identification from the predicted anonymity histogram.Type: GrantFiled: January 9, 2017Date of Patent: August 13, 2019Assignee: PRIVACY ANALYTICS INC.Inventors: Martin Scaiano, Andrew Baker, Stephen Korte
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Patent number: 10318763Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.Type: GrantFiled: December 20, 2016Date of Patent: June 11, 2019Assignee: PRIVACY ANALYTICS INC.Inventors: Sean Rose, Weilong Song, Martin Scaiano
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Patent number: 10242213Abstract: System and method to produce an anonymized cohort, members of the cohort having less than a predetermined risk of re-identification. The system includes a user-facing communication interface to receive an anonymized cohort request comprising traits to include in members of the cohort; a data source-facing communication channel to query a data source, to find anonymized records that possess at least some of the requested traits; and a processor programmed to carry out the instructions of: forming a dataset from at least some of the anonymized records; calculating a risk of re-identification of the anonymized records in the dataset based upon the data query; perturbing anonymized records in the dataset that exceed a predetermined risk of re-identification, until the risk of re-identification is not greater than the pre-determined threshold, to produce the anonymized cohort; and providing, via a user-facing communication channel, the anonymized cohort.Type: GrantFiled: September 21, 2016Date of Patent: March 26, 2019Assignee: PRIVACY ANALYTICS INC.Inventors: Martin Scaiano, Andrew Baker, Stephen Korte, Khaled El Emam
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Publication number: 20180173893Abstract: System and method to produce an anonymized cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits for the anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and grouping the dataset in time into a first boundary group, a second boundary group, and one or more non-boundary groups temporally between the first boundary group and second boundary group. For each non-boundary group, calculating maximum time limits the non-boundary group can be time-shifted without overlapping an adjacent group, calculating a group jitter amount, capping the group jitter amount by the maximum time limits and by respective predetermined jitter limits, and jittering said non-boundary group by the capped group jitter amount to produce an anonymized dataset. Return the anonymized dataset.Type: ApplicationFiled: December 20, 2016Publication date: June 21, 2018Inventors: Sean Rose, Weilong Song, Martin Scaiano
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Publication number: 20180114037Abstract: There is provided a system and method executed by a processor for estimating re-identification risk of a single individual in a dataset. The individual, subject or patient is described by a data subject profile such as a record in the dataset. A population distribution is retrieved from a storage device, the population distribution is determined by one or more quasi-identifying fields identified in the data subject profile. An information score is then assigned to each quasi-identifying (QI) value of the one or more quasi-identifying fields associated with the data subject profile. The assigned information scores of the quasi-identifying values for the data subject profile are aggregated into an aggregated information value. An anonymity value is then calculated from the aggregated information value and a size of a population associated with the dataset. A re-identification metric for the individual from the anonymity value is then calculated.Type: ApplicationFiled: April 1, 2016Publication date: April 26, 2018Inventors: Martin SCAIANO, Stephen KORTE, Andrew BAKER, Geoffrey GREEN, Khaled EL EMAM, Luk ARBUCKLE
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Publication number: 20170177907Abstract: A computer-implemented system and method to reduce re-identification risk of a data set. The method includes the steps of retrieving, via a database-facing communication channel, a data set from a database communicatively coupled to the processor, the data set selected to include patient medical records that meet a predetermined criteria; identifying, by a processor coupled to a memory, direct identifiers in the data set; identifying, by the processor, quasi-identifiers in the data set; calculating, by the processor, a first probability of re-identification from the direct identifiers; calculating, by the processor, a second probability of re-identification from the quasi-direct identifiers; perturbing, by the processor, the data set if one of the first probability or second probability exceeds a respective predetermined threshold, to produce a perturbed data set; and providing, via a user-facing communication channel, the perturbed data set to the requestor.Type: ApplicationFiled: March 7, 2017Publication date: June 22, 2017Inventors: Martin Scaiano, Grant Middleton, Varada Kolhatkar, Khaled El Emam
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Publication number: 20170124351Abstract: System and method to predict risk of re-identification of a cohort if the cohort is anonymized using a de-identification strategy. An input anonymity histogram and de-identification strategy is used to predict the anonymity histogram that would result from applying the de-identification strategy to the dataset. System embodiments compute a risk of re-identification from the predicted anonymity histogram.Type: ApplicationFiled: January 9, 2017Publication date: May 4, 2017Inventors: Martin Scaiano, Andrew Baker, Stephen Korte
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Publication number: 20170103232Abstract: System and method to produce an anonymized cohort, members of the cohort having less than a predetermined risk of re-identification. The method includes receiving a data query of requested traits to request in an anonymized cohort, querying a data source to find records that possess at least some of the traits, forming a dataset from at least some of the records, and calculating an anonymity histogram of the dataset. For each patient record within the dataset, the method anonymizes the dataset by calculating using a threshold selector whether a predetermined patient profile within the dataset should be perturbed, calculating using a value selector whether a value within the indicated patient profile should be perturbed, and suppressing an indicated value within the indicated patient profile. The anonymized dataset then is returned.Type: ApplicationFiled: December 23, 2016Publication date: April 13, 2017Inventors: Martin Scaiano, Andrew Baker, Stephen Korte
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Publication number: 20170083719Abstract: System and method to produce an anonymized cohort, members of the cohort having less than a predetermined risk of re-identification. The system includes a user-facing communication interface to receive an anonymized cohort request comprising traits to include in members of the cohort; a data source-facing communication channel to query a data source, to find anonymized records that possess at least some of the requested traits; and a processor programmed to carry out the instructions of: forming a dataset from at least some of the anonymized records; calculating a risk of re-identification of the anonymized records in the dataset based upon the data query; perturbing anonymized records in the dataset that exceed a predetermined risk of re-identification, until the risk of re-identification is not greater than the pre-determined threshold, to produce the anonymized cohort; and providing, via a user-facing communication channel, the anonymized cohort.Type: ApplicationFiled: September 21, 2016Publication date: March 23, 2017Inventors: Martin Scaiano, Andrew Baker, Stephen Korte, Khaled El Emam