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De-identification is the process used to prevent someone's personal identity from being revealed. For example, data produced during human subject research might be de-identified to preserve the privacy of research participants.
22 de nov. de 2021 · De-identified data is data that is not reasonably associated with an individual and has technical safeguards to prevent reidentification. Learn how different states, such as California, Virginia and Colorado, define and regulate de-identified data in their privacy statutes.
This whitepaper covers classic de-identification techniques like record suppression, cell suppression, sub-sampling and aggregation as well as the pros and cons of Safe Harbour and Expert De-identification strategies. Make sure to read De-identification 101, 301 and 401 to get the full picture.
De-identification removes identifying information from a dataset so that individual data cannot be linked with specific individuals. De-identification can reduce the privacy risk associated with collecting, processing, archiving, distributing or publishing information.
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1 de mai. de 2020 · De-identified data are data that have no direct or indirect identifiers or codes linking them to individual subjects. Learn how to distinguish de-identified data from coded and anonymous data, and how to apply them in your IRB applications.
It's essential that data remains confidential and personal information is removed. Learn more about this process, known as de-identification.
In this piece for Privacy Tech, Immuta’s Alfred Rossi, Andrew Burt and Sophie Stalla-Bourdillon look to clarify the definition of these practices, help distinguish between direct and indirect identifiers, and offer some considerations for organizations that want to properly deidentify their data. Read More.
