PRIVACY-PRESERVING COMPUTING ON SUBJECT DATA USED TO DEVELOP ARTIFICIAL INTELLIGENCE TOOLS

The present disclosure relates to techniques for privacy-preserving computing to protect a subject's privacy while using the subject's data for secondary purposes such as training and deploying artificial intelligence tools. Particularly, aspects are directed to receiving, at a local serve...

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Main Authors Dridi, Abdesslem, Jalal, Niaz Ahsan
Format Patent
LanguageEnglish
Published 17.08.2023
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Abstract The present disclosure relates to techniques for privacy-preserving computing to protect a subject's privacy while using the subject's data for secondary purposes such as training and deploying artificial intelligence tools. Particularly, aspects are directed to receiving, at a local server, subject data regarding a first subject, performing, by the local server, a de-identifying operation, an anonymizing operation, or both on the subject data, sending the subject data to a remote server, receiving a production model from the remote server, the production model including parameters derived in part from the processed subject data, receiving, at the local server, subsequent data regarding a second subject, inputting, by the local server, the subsequent data into the production model to analyze the subsequent data and generate an inference or prediction from the analysis of the subsequent data; and sending, by the local server, the inference or the prediction to a computing device.
AbstractList The present disclosure relates to techniques for privacy-preserving computing to protect a subject's privacy while using the subject's data for secondary purposes such as training and deploying artificial intelligence tools. Particularly, aspects are directed to receiving, at a local server, subject data regarding a first subject, performing, by the local server, a de-identifying operation, an anonymizing operation, or both on the subject data, sending the subject data to a remote server, receiving a production model from the remote server, the production model including parameters derived in part from the processed subject data, receiving, at the local server, subsequent data regarding a second subject, inputting, by the local server, the subsequent data into the production model to analyze the subsequent data and generate an inference or prediction from the analysis of the subsequent data; and sending, by the local server, the inference or the prediction to a computing device.
Author Dridi, Abdesslem
Jalal, Niaz Ahsan
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Snippet The present disclosure relates to techniques for privacy-preserving computing to protect a subject's privacy while using the subject's data for secondary...
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COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
Title PRIVACY-PRESERVING COMPUTING ON SUBJECT DATA USED TO DEVELOP ARTIFICIAL INTELLIGENCE TOOLS
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