Learning to transform sensitive data with variable distribution preservation

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United States of America Patent

PATENT NO 11647004
APP PUB NO 20220311749A1
SERIAL NO

17211191

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Abstract

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Preserving distributions of data values of a data asset in a data anonymization operation is provided. Anonymizing data values is performed by transforming sensitive data in a set of columns over rows of the data asset while preserving distribution of the data values in the set of transformed columns to a defined degree using a set of autoencoders and loss function. The autoencoders are base trained from preexisting data in a data assets catalog and actively trained during data dissemination. Parametric coefficients of the loss function are configured and the threshold is generated using policies from an enforcement decision for the data asset and data consumer. The loss function value of a selected row is compared to the threshold. Transformed data values of the selected row are transcribed to an output row when the loss function value is greater than the threshold and disseminated to the data consumer.

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Patent Owner(s)

  • INTERNATIONAL BUSINESS MACHINE CORPORATION

International Classification(s)

Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Aggarwal, Aniya New Delhi, IN 10 41
Desai, Rajesh M San Jose, US 47 265
Kundu, Ashish San Jose, US 182 3288
Natarajan, Arjun Old Tappan, US 21 79
Payne, Joshua F San Antonio, US 9 19
Qiao, Mu Belmont, US 75 573
Raphael, Roger C San Jose, US 60 551

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