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 removing or modifying identifying information from a dataset to prevent individuals from being identified. This process aims to preserve the overall utility of the data while minimizing privacy risks. By stripping away direct identifiers such as names, addresses, and phone numbers, organizations can still derive valuable insights from the data without compromising individuals’ privacy.

Pseudonymity, on the other hand, involves replacing identifying information with pseudonyms or aliases. This method allows individuals to access services or participate in activities without disclosing their real identities. By using pseudonyms, individuals can still enjoy a level of anonymity while maintaining a degree of personalization and convenience.

Both data de-identification and pseudonymity have proven to be effective in protecting individuals’ privacy and minimizing the risk of unauthorized access to sensitive information. However, their usefulness depends on various factors such as the quality of the de-identification process, the level of anonymity provided by pseudonyms, and the security measures in place to prevent re-identification.

One of the key benefits of data de-identification is that it allows organizations to share data for research, analytics, and other purposes without violating privacy regulations. By anonymizing the data, organizations can comply with data protection laws while still leveraging the information for valuable insights. Data de-identification also helps reduce the risks associated with data breaches, as stolen or leaked data would be much less valuable without identifiers.

Similarly, pseudonymity offers individuals a layer of privacy while still allowing them to engage in online activities. By using pseudonyms, individuals can minimize the collection of personal information by online services, reduce the risk of identity theft, and protect their online reputation. Pseudonyms also provide a level of freedom for individuals to express themselves without fear of being targeted or judged based on their real identities.

However, despite their benefits, data de-identification and pseudonymity are not foolproof measures for protecting privacy. Re-identification techniques and advancements in data analytics have shown that even anonymized or pseudonymized data can be linked back to individuals under certain circumstances. This risk highlights the importance of implementing robust security measures, strict data governance practices, and ongoing monitoring to prevent privacy breaches.

In conclusion, data de-identification and pseudonymity can be valuable tools in protecting individuals’ privacy and minimizing privacy risks associated with data sharing and online activities. While they are not foolproof solutions, they offer a level of protection that can help organizations comply with regulations and individuals maintain a level of anonymity in the digital world. As technology continues to evolve, it is essential to stay vigilant and enforce best practices to ensure the effectiveness of these privacy measures.

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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