# References - De-Identification Profile v0.0.1-current

* [**Table of Contents**](toc.md)
* **References**

## References

1. ISO 25237. (2017).**Health informatics — Pseudonymization**(ISO 25237:2017; Number ISO 25237:2017). International Organization for Standardization.[https://www.iso.org/standard/63553.html](https://www.iso.org/standard/63553.html)
1. ISO/IEC 20889. (2018).**Privacy enhancing data de-identification terminology and classification of techniques**(Standard ISO/IEC 20889:2018(E); Number ISO/IEC 20889:2018(E)). International Organization for Standardization.[https://www.iso.org/standard/69373.html](https://www.iso.org/standard/69373.html)
1. GDPR. (2016).**Regulation (EU) 2016/679 of the European Parliament and of the Council**. European Parliament and Council of the European Union.[https://data.europa.eu/eli/reg/2016/679/oj](https://data.europa.eu/eli/reg/2016/679/oj)
1. PIPL. (2021).**Personal Information Protection Law of the People’s Republic of China**. National People’s Congress of the People’s Republic of China (NPC).[http://en.npc.gov.cn.cdurl.cn/2021-12/29/c_694559.htm](http://en.npc.gov.cn.cdurl.cn/2021-12/29/c_694559.htm)
1. NIST 800-188. (2023).**De-identifying Government Datasets**(Special Publication No. 800-188; Numbers 800-188). National Institute of Standards and Technology.[https://doi.org/10.6028/nist.sp.800-188](https://doi.org/10.6028/nist.sp.800-188)
1. European Data Protection Board. (2025).**Guidelines 01/2025 on Pseudonymisation**.[https://www.edpb.europa.eu/system/files/2025-01/edpb_guidelines_202501_pseudonymisation_en.pdf](https://www.edpb.europa.eu/system/files/2025-01/edpb_guidelines_202501_pseudonymisation_en.pdf)
1. Information Commissioner’s Office. (2025).**Pseudonymisation**. Information Commissioner’s Office.[https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/data-sharing/anonymisation/pseudonymisation/#pseudonymiseddatastillpersonal](https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/data-sharing/anonymisation/pseudonymisation/#pseudonymiseddatastillpersonal)
1. Office for Civil Rights. (2025).**Methods for De-identification of PHI**. HHS.gov.[https://www.hhs.gov/hipaa/for-professionals/special-topics/de-identification/index.html#rationale](https://www.hhs.gov/hipaa/for-professionals/special-topics/de-identification/index.html#rationale)
1. Hintze, M. (2017). Viewing the GDPR through a de-identification lens: a tool for compliance, clarification, and consistency.**International Data Privacy Law**,**8**(1), 86–101.[https://doi.org/10.1093/IDPL/IPX020](https://doi.org/10.1093/IDPL/IPX020)
1. U.S. Congress. (1996).**Health Insurance Portability and Accountability Act of 1996**. Public Law 104-191.[https://www.govinfo.gov/content/pkg/PLAW-104publ191/pdf/PLAW-104publ191.pdf](https://www.govinfo.gov/content/pkg/PLAW-104publ191/pdf/PLAW-104publ191.pdf)
1. GB/T 42460. (2023).**Information security technology - Guide for evaluating the effectiveness of personal information de-identification**(Standard GB/T 42460—2023; Number GB/T 42460—2023). State Administration for Market Regulation Standardization Administration of China.[https://www.iso.org/standard/69373.html](https://www.iso.org/standard/69373.html)
1. University of Manchester. (2024).**Anonymisation decision-making framework: European practitioners’ guide**(2nd ed.). University of Manchester.[https://ukanon.net/wp-content/uploads/2024/01/adf-2nd-edition-european-practitioners-guide-final-version-cover-2024-version-2.pdf](https://ukanon.net/wp-content/uploads/2024/01/adf-2nd-edition-european-practitioners-guide-final-version-cover-2024-version-2.pdf)
1. National Electrical Manufacturers Association. (2025).**DICOM Part 15, Annex E: Security and System Management Profiles — Attribute Confidentiality Profiles**(PS3.15 Annex E; Number PS3.15 Annex E). National Electrical Manufacturers Association.[https://dicom.nema.org/medical/dicom/current/output/chtml/part15/chapter_E.html](https://dicom.nema.org/medical/dicom/current/output/chtml/part15/chapter_E.html)
1. ISO/IEC 27559. (2022).**Information security, cybersecurity and privacy protection — Privacy enhancing data de-identification framework**(ISO/IEC 27559:2022; Number ISO/IEC 27559:2022). International Organization for Standardization.[https://www.iso.org/standard/71677.html](https://www.iso.org/standard/71677.html)
1. ISO 27799. (2025).**Health informatics — Information security management in health using ISO/IEC 27002**. International Organization for Standardization.[https://www.iso.org/standard/86754.html](https://www.iso.org/standard/86754.html)
1. ISO/TS 22220. (2011).**Health informatics — Identification of subjects of care**(ISO/TS 22220:2011; Number ISO/TS 22220:2011). International Organization for Standardization.[https://www.iso.org/standard/44439.html](https://www.iso.org/standard/44439.html)
1. Article 29 Data Protection Working Party. (2014, April 10).**Opinion 05/2014 on anonymisation techniques (WP216)**. European Commission. https://ec.europa.eu/justice/article-29/documentation/opinion-recommendation/files/2014/wp216_en.pdf
1. HP.**Efficient signature schemes supporting redaction, pseudonymization, and data deidentification.****HP.**[HPL-2007-191](http://hpl.hp.com/techreports/2007/HPL-2007-191.pdf)
1. Schneier, Bruce.**Commentary on the Importance of a Systemic Approach to Security.**Bruce Schneier.[Essay-028](http://www.schneier.com/essay-028.html)
1. UK Redaction Toolkit.**A United Kingdom government document describing a toolkit for removing content prior publication for various legal reasons.**[REDACTION GUIDELINES FOR THE EDITING OF EXEMPT INFORMATION FROM PAPER AND ELECTRONIC DOCUMENTS PRIOR TO RELEASE](http://www.nationalarchives.gov.uk/documents/information-management/redaction_toolkit.pdf)
1. DICOM.[DICOM](https://www.dicomstandard.org/current)current publication
1. DICOM Part 15 Annex E.**Discusses clinical trials, double-blinding, traceability (relinking) to original content, preserving data needed for the trial.**[DICOM Part 15, Annex E](https://dicom.nema.org/medical/dicom/current/output/chtml/part15/chapter_E.html)current publication
1. Moehrke.**De-Identification is Highly Contextual**. (2009)[De-Identification is highly contextual](http://healthcaresecprivacy.blogspot.com/2009/10/de-identification-is-highly-contextual.html)
1. HITSP.**HITSP Biosurveillance Use Case Presentation**. Lists summary of units of data exchange and values that should be pseudonymized.[HITSP Biosurveillance Use Case presentation](http://hitsp.wikispaces.com/Biosurveillance+Use+Case)
1. NIH Biosurveillance Test Case Scenarios.[Presentation by David Dobbs on the Biosurveillance Use Case and Minimum Data Elements](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2995626/)
1. NHN Biosurveillance Test Scenarios.**NHN Testing Work Group document *Biosurveillance Test Case Scenarios**. 2008-10-03.xls* file, draft.
1. Dresden Anonymity.**A proposed vocabulary for pseudonymization and related concepts**.[Anonymity, Unlinkability, Undetectability, Unobservability, Pseudonymity, and Identity Management – A onsolidated Proposal for Terminology* (Version v0.31 Feb. 15, 2008)](http://dud.inf.tu-dresden.de/literatur/Anon_Terminology_v0.31.pdf)
1. MIT Reidentification.**Shows that a large percentage of people can be re-identified with Date-of-Birth, Current ZIP Code, and Sex**.[Reidentification of Individuals in Chicago's Homicide Database A Technical and Legal Study](http://web.mit.edu/sem083/www/assignments/reidentification.html#_Toc354562093)
1. European Medicines Agency. (2025, May 14).**External guidance on the implementation of the European Medicines Agency Policy 0070 on the publication of clinical data for medicinal products for human use**(Version 1.5).[https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/external-guidance-implementation-european-medicines-agency-policy-publication-clinical-data-medicinal-products-human-use-version-15_en.pdf](https://www.ema.europa.eu/en/documents/regulatory-procedural-guideline/external-guidance-implementation-european-medicines-agency-policy-publication-clinical-data-medicinal-products-human-use-version-15_en.pdf)
1. Information and Privacy Commissioner of Ontario. (2016, June).**De-identification Guidelines for Structured Data**.[https://www.ipc.on.ca/sites/default/files/legacy/2016/08/Deidentification-Guidelines-for-Structured-Data.pdf](https://www.ipc.on.ca/sites/default/files/legacy/2016/08/Deidentification-Guidelines-for-Structured-Data.pdf)
1. Branson, J., Good, N., Chen, JW. et al. (2020). Evaluating the re-identification risk of a clinical study report anonymized under EMA Policy 0070 and Health Canada Regulations.**Trials**21, 200.[https://doi.org/10.1186/s13063-020-4120-y](https://doi.org/10.1186/s13063-020-4120-y)
1. Sweeney, L. (2002). k-anonymity: A model for protecting privacy.**International Journal on Uncertainty, Fuzziness and Knowledge-Based Systems**, 10(05), 557-570.[https://doi.org/10.1142/s0218488502001648](https://doi.org/10.1142/s0218488502001648)
1. Dwork, C., & Roth, A. (2014). The algorithmic foundations of differential privacy.**Foundations and Trends® in Theoretical Computer Science**, 9(3-4), 211-407.[https://doi.org/10.1561/0400000042](https://doi.org/10.1561/0400000042)
1. El Emam, K. (2013).**Guide to the de-identification of personal health information**. Auerbach Publications.[https://doi.org/10.1201/b14754](https://doi.org/10.1201/b14754)
1. Shahid, A., Bazargani, M. H., Banahan, P., Mac Namee, B., Kechadi, T., Treacy, C., Regan, G., & MacMahon, P. (2022). A Two-Stage De-Identification Process for Privacy-Preserving Medical Image Analysis.**Healthcare (Basel, Switzerland)**,**10**(5), 755. https://doi.org/10.3390/healthcare10050755
1. Mayer, D. A., Teubert, D., Wetzel, S., & Meyer, U. (2011). Implementation and performance evaluation of privacy-preserving fair reconciliation protocols on ordered sets. In Proceedings of the First ACM Conference on Data and Application Security and Privacy (pp. 109–120). Association for Computing Machinery. https://doi.org/10.1145/1943513.1943529
1. Domingo-Ferrer, J., & Mateo-Sanz, J. M. (2002). Practical data-oriented microaggregation for statistical disclosure control. IEEE Transactions on Knowledge and Data Engineering, 14(1), 189–201. https://doi.org/10.1109/69.979982
1. Poulis, G., Loukides, G., Gkoulalas-Divanis, A., & Skiadopoulos, S. (2013). Anonymizing Data with Relational and Transaction Attributes. ECML/PKDD.
1. Liu, K., & Terzi, E. (2008). Towards identity anonymization on graphs.**Proceedings of the 2008 ACM SIGMOD international conference on Management of data**.
1. NIST. (2024).**Guidelines for Evaluating Differential Privacy Guarantees**(Special Publication No. 800-226). National Institute of Standards and Technology.[https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-226.pdf](https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-226.pdf)
1. Future of Privacy Forum. (2020, April). A practical path toward genetic privacy. https://fpf.org/wp-content/uploads/2020/04/APracticalPathTowardGeneticPrivacy_April2020.pdf
1. IHE International. (2025). IHE radiology technical framework, volume 1: Integration profiles (Rev. 23.0). https://www.ihe.net/uploadedFiles/Documents/Radiology/IHE_RAD_TF_Vol1.pdf
1. O'Keefe, C., Otorepec, S., Elliot, M., Mackey, E., & O'Hara, K. (2017).**The de-identification decision-making framework**. CSIRO Data61. https://doi.org/10.4225/08/59c169433efd4
1. Information and Privacy Commissioner of Ontario. (2016). De-identification guidelines for structured data. https://www.ipc.on.ca/sites/default/files/legacy/2016/08/Deidentification-Guidelines-for-Structured-Data.pdf
1. Jiang, Y., Mosquera, L., Jiang, B., Kong, L., & El Emam, K. (2022). Measuring re-identification risk using a synthetic estimator to enable data sharing.**PLOS ONE**,**17**(6), e0269097. https://doi.org/10.1371/journal.pone.0269097

