Privacy and modeling preserved data sharing
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United States of America Patent
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Aug 27, 2019
Grant Date -
Sep 29, 2016
app pub date -
Jul 10, 2015
filing date -
Mar 24, 2015
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Abstract
A method for generating a classification model using original data that is sensitive or private to a data owner. The method includes: receiving, from one or more entities, a masked data set having masked data corresponding to the original sensitive data, and further including a masked feature label set for use in classifying the masked data contents; forming a shared data collection of the masked data and the masked feature label sets received; and training, by a second entity, a classification model from the shared masked data and feature label sets, wherein the classification model learned from the shared masked data and feature label sets is the same as a classification model learned from the original sensitive data. The sensitive features and labels cannot be reliably recovered even when both the masked data and the learning algorithm are known.
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