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Search Search CSRC MENU Search Search Projects Publications Expand or Collapse Drafts for Public Comment All Public Drafts Final Pubs FIPS (standards) Special Publications (SP s ) IR (interagency/internal reports) CSWP (cybersecurity white papers) ITL Bulletins Project Descriptions Journal Articles Conference Papers Books Topics Expand or Collapse Security & Privacy Applications Technologies Sectors Laws & Regulations Activities & Products News & Updates Events Glossary About CSRC Expand or Collapse Computer Security Division Cryptographic Technology Software Security Group Hardware Security Group Security Engineering and Risk Management Applied Cybersecurity Division Cybersecurity and Privacy Applications National Cybersecurity Center of Excellence (NCCoE) National Initiative for Cybersecurity Education (NICE) Contact Us Information Technology Laboratory Computer Security Resource Center Publications NIST SP 800-188 De-Identifying Government Datasets: Techniques and Governance Share to Facebook Share to X Share to LinkedIn Share ia Email Documentation Topics Date Published: September 2023 Author(s) Simson Garfinkel (NIST) , Barbara Guttman (NIST) , Joseph Near (University of Vermont) , Aref Dajani (U.S. Census Bureau) , Phyllis Singer (U.S. Census Bureau) Abstract De-identification is a general term for any process of removing the association between a set of identifying data and the data subject. This document describes the use of deidentification with the goal of preventing or limiting disclosure risks to individuals and establishments while still allowing for the production of meaningful statistical analysis. Government agencies can use de-identification to reduce the privacy risk associated with collecting, processing, archiving, distributing, or publishing government data. Previously, NIST IR 8053, "De-Identification of Personal Information," provided a detailed survey of deidentification and re-identification techniques. This document provides specific guidance to government agencies that wish to use de-identification. Before using de-identification, agencies should evaluate their goals for using de-identification and the potential risks that releasing de-identified data might create. Agencies should decide upon a data-sharing model, such as publishing de-identified data, publishing synthetic data based on identified data, providing a query interface that incorporates de-identification, or sharing data in non-public protected enclaves. Agencies can create a Disclosure Review Board to oversee the process of de-identification. They can also adopt a de-identification standard with measurable performance levels and perform re-identification studies to gauge the risk associated with de-identification. Several specific techniques for de-identification are available, including de-identification by removing identifiers, transforming quasi-identifiers, and generating synthetic data using models. People who perform de-identification generally use special-purpose software tools to perform the data manipulation and calculate the likely risk of re-identification. However, not all tools that merely mask personal information provide sufficient functionality for performing de-identification. This document also includes an extensive list of references, a glossary, and a list of specific de-identification tools, which is only included to convey the range of tools currently available and is not intended to imply a recommendation or endorsement by NIST. De-identification is a general term for any process of removing the association between a set of identifying data and the data subject. This document describes the use of deidentification with the goal of preventing or limiting disclosure risks to individuals and establishments while still allowing... See full abstract De-identification is a general term for any process of removing the association between a set of identifying data and the data subject. This document describes the use of deidentification with the goal of preventing or limiting disclosure risks to individuals and establishments while still allowing for the production of meaningful statistical analysis. Government agencies can use de-identification to reduce the privacy risk associated with collecting, processing, archiving, distributing, or publishing government data. Previously, NIST IR 8053, "De-Identification of Personal Information," provided a detailed survey of deidentification and re-identification techniques. This document provides specific guidance to government agencies that wish to use de-identification. Before using de-identification, agencies should evaluate their goals for using de-identification and the potential risks that releasing de-identified data might create. Agencies should decide upon a data-sharing model, such as publishing de-identified data, publishing synthetic data based on identified data, providing a query interface that incorporates de-identification, or sharing data in non-public protected enclaves. Agencies can create a Disclosure Review Board to oversee the process of de-identification. They can also adopt a de-identification standard with measurable performance levels and perform re-identification studies to gauge the risk associated with de-identification. Several specific techniques for de-identification are available, including de-identification by removing identifiers, transforming quasi-identifiers, and generating synthetic data using models. People who perform de-identification generally use special-purpose software tools to perform the data manipulation and calculate the likely risk of re-identification. However, not all tools that merely mask personal information provide sufficient functionality for performing de-identification. This document also includes an extensive list of references, a glossary, and a list of specific de-identification tools, which is only included to convey the range of tools currently available and is not intended to imply a recommendation or endorsement by NIST. Hide full abstract Keywords data life cycle ; de-identification ; differential privacy ; direct identifiers ; Disclosure Review Board ; k-anonymity ; privacy ; pseudonymization ; quasi-identifiers ; re-identification ; synthetic data ; The Five Safes Control Families Program Management ; Risk Assessment ; System and Communications Protection Documentation Publication: https://doi.org/10.6028/NIST.SP.800-188 Download URL Supplemental Material: None available Document History: 08/25/16: SP 800-188 (Draft) 12/15/16: SP 800-188 (Draft) 11/15/22: SP 800-188 (Draft) 09/14/23: SP 800-188 (Final) Topics Security and Privacy privacy Laws and Regulations E-Government Act HEADQUARTERS 100 Bureau Drive Gaithersburg, MD 20899 X (link is external) facebook (link is external) linkedin (link is external) instagram (link is external) youtube (link is external) rss govdelivery (link is external) Want updates about CSRC and our publications? 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