De-identification Protocol for Open Data

The International Association of Privacy Professionals, or IAPP, has published a new article from Privacy Analytics’ CEO, Dr Khaled El Emam, A de-identification protocol for open data. In his piece, Dr El Emam discusses that while there are calls for open data initiatives, there must also be a standard for maintaining privacy. By applying a de-identification protocol to any data sharing initiative, organizations can preserve privacy and be compliant with legal regulations and individuals can be assured they remain anonymous. He outlines five key steps to this protocol:

  1. Classify Variables (Determine if you are dealing with identifiers that immediately identify an individual (like name or Social Security number) or indirectly (DOB, zip code).)
  2. Pseudonymize or Remove Direct Identifiers
  3. K-Anonymize the Indirect Identifiers
  4. Perform a Motivated Intruder Test (Ensuring you have taken the appropriate steps to preserve privacy from Step 3.)
  5. Update the De-identification (To include the results of Step 4.)

To learn more, please read the full article here.

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