/ppmf_12.2_reid

Simulation study of re-identification risk in ppmf_20210428_eps12-2_P

Primary LanguageTeXMIT LicenseMIT

Simulation study of re-identification risk in ppmf_20210428_eps12-2_P

Plan of Work:

For each county, just for the people in households (not gq):

  1. Load individual person data synthesized for that county in re-id exercise (df_synth)

  2. Split df_synth it into (a) simulated external data (df_sim) and (b) hold-out validation data (df_test)

  3. Load corresponding county of privacy protected person data from PL-74 demonstration product (df_ppmf)

  4. merge df_sim and df_ppmf on their common fields, e.g. track, block, and voting_age

  5. see how many individuals in df_sim have a unique match, and how many individuals in df_sim have a unique race or ethnicity in the matched ppmf data

  6. for the individuals in df_sim with a unique match or with matches with a unique race/ethnicity, see how often this linked data is the same as the value in the validation data in df_test

Since the PPMF is based on the pre-swapped data, step (6) is perhaps not meaningful. If instead of loading df_ppmf, I simulate it from the same df_synth data, I can make it meaningful, and also sweep across values of epsilon. And then compare at epsilon empirical found from PPMF.