Enforce k-anonymity on a synthetic dataset (output guarantee)

Shapes the synthetic output so that no quasi-identifier combination appears in fewer than k records. Direct identifiers are removed. Quasi-identifiers are coarsened step-by-step and any residual cell still below k has its QI values blanked (NA). Operates on the output only.

Usage

enforce_kanon(synthetic, roles, k = 5, max_steps = 6L, max_suppress_frac = 0.2)

Arguments

synthetic

A synthetic data frame.

roles

A roles object/data frame with variable + disclosure_role.

k

Minimum cell size (default 5).

max_steps

Maximum coarsening iterations (default 6).

max_suppress_frac

Feasibility backstop. If satisfying k over the quasi-identifier set would require blanking more than this fraction of rows, k-anonymity is treated as infeasible for the chosen quasi-identifier (QI) set: the coarsening and suppression steps are not applied, the synthetic output is returned populated, and a warning explains that no k-anonymity protection was applied to that output. Default 0.2.

Value

The shaped synthetic data frame, with an attribute kanon recording the achieved state (smallest_cell, suppressed_cells, suppressed_rows, suppressed_row_frac, qi_cols, k, infeasible). suppressed_rows/suppressed_row_frac count actual blanked rows across the QI columns – distinct from suppressed_cells, which counts the number of distinct QI combinations folded into suppression. The two can differ a lot: reaching k can require absorbing a few whole neighbouring cells (suppression works at cell granularity, not row granularity), and a handful of small cells sitting next to one dominant cell can end up suppressing most or all of a QI column even though only a few original cells were actually below k.