Data De-identification and Pseudonymity Statistics


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Data De-Identification And Pseudonymity Statistics 2023: Facts about Data De-Identification And Pseudonymity outlines the context of what’s happening in the tech world.

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Top Data De-Identification And Pseudonymity Statistics 2023

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Data De-Identification And Pseudonymity “Latest” Statistics

  • According to one well-known research, it is feasible to individually identify 87 percent of the US population with only three data points: a five-digit ZIP code, gender, and date of birth.[1]
  • When using the Safe Harbor de-identification technique, the first three digits of a ZIP code are converted to 000 for any such geographic area with 20,000 or fewer persons.[2]
  • The technique used by Rocher, Hendrickx, and Montjoye achieves AUC values for predicting individual uniqueness ranging from 0.84 to 0.97 on 210 populations, with a low false-discovery rate.[3]
  • Rocher, Hendrickx, and Montjoye discovered that 99.98% of Americans could be successfully re-identified in any dataset using 15 demographic parameters using our approach.[3]
  • According to a recent poll, more than 72% of US residents are concerned about sharing personal information online.[3]
  • Journalists re-identified politicians in an anonymized browser history dataset of 3 million German residents in 2016, revealing their medical information and sexual preferences.[3]
  • The Australian Department of Health made de-identified medical information available to the public for 10% of the population, only for researchers to re-identify them six weeks later.[3]
  • 15 demographic characteristics would distinguish 99.98% of persons in Massachusetts.[3]
  • According to 2010 data, 19% of healthcare businesses had a data breach in the preceding year (HIMSS Analytics, 2010).[4]
  • When using the Safe Harbor method of de-identification, all elements of dates (except year) for dates that are directly related to an individual, such as birth date, admission date, discharge date, death date, and all ages over 89, as well as all elements of dates (including year) indicative of such age, may be aggregated into a single category of age 90 or older.[2]

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How Useful is Data De Identification and Pseudonymity

Data de-identification involves the process of removing personally identifiable information (PII) from a dataset, while pseudonymity substitutes identifiable information with pseudonyms or unique identifiers. These techniques are commonly used to protect the privacy of individuals while still permitting the sharing and analysis of sensitive data for research, analytics, and other purposes. By anonymizing data, organizations can preserve the privacy of individuals while still benefiting from the valuable insights that data analysis can provide.

One of the primary benefits of data de-identification and pseudonymity is the ability to balance privacy with utility. By removing or obfuscating identifying information, organizations can reduce the risk of re-identifying individuals in a dataset. This not only protects the privacy of individuals but also mitigates the potential for data breaches, identity theft, and other malicious activities. At the same time, de-identified data can still be used for a variety of valuable purposes, such as medical research, market analysis, and public policy evaluation.

Moreover, data de-identification and pseudonymity can help organizations comply with regulations and standards regarding data protection and privacy. Many jurisdictions have established laws and guidelines that dictate how organizations must handle sensitive data, including requirements for de-identification and pseudonymization. By implementing these techniques, organizations can demonstrate their commitment to safeguarding data privacy and comply with legal obligations, thereby reducing the risk of regulatory penalties and sanctions.

Another advantage of data de-identification and pseudonymity is their versatility and applicability across different industries and sectors. Whether in healthcare, finance, education, or government, organizations can benefit from anonymizing data to protect privacy and enhance security. By incorporating de-identification processes into their data management practices, organizations can ensure that sensitive information is safeguarded while still enabling the legitimate use of data for analysis and decision-making.

Despite the advantages of data de-identification and pseudonymity, it is essential to recognize their limitations and potential drawbacks. While these techniques can help protect privacy and security, they are not foolproof and may not always prevent re-identification of individuals in a dataset. As technology advances and new data analysis methods emerge, the risk of re-identification could increase, posing challenges for maintaining data anonymity over time.

In conclusion, data de-identification and pseudonymity play a vital role in safeguarding privacy and security in the digital age. By anonymizing sensitive data and substituting identifiable information with pseudonyms, organizations can balance the need for privacy with the benefits of data analysis and sharing. While these techniques are not without their limitations, they represent essential tools for ensuring the responsible and ethical handling of personal information in today’s data-driven world.

Reference

  1. iapp – https://iapp.org/news/a/looking-to-comply-with-gdpr-heres-a-primer-on-anonymization-and-pseudonymization/
  2. hhs – https://www.hhs.gov/hipaa/for-professionals/privacy/special-topics/de-identification/index.html
  3. nature – https://www.nature.com/articles/s41467-019-10933-3
  4. nih – https://www.ncbi.nlm.nih.gov/books/NBK285994/

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