k-anonymity verification — morie_k_anonymity

Checks whether a data.frame satisfies k-anonymity over the supplied quasi-identifier columns. A dataset is k-anonymous if every combination of quasi-identifier values appears in at least k rows.

Usage

morie_k_anonymity_verify(data, quasi_identifiers, k = 5)

Arguments

data: data.frame.
quasi_identifiers: Character vector of column names.
k: Minimum equivalence-class size. Default 5 (a common public-health / open-data threshold).

Value

A list with class "morie_k_anon" containing:

satisfies: logical, whether the dataset is k-anonymous.
k: the threshold used.
min_class_size: integer, size of the smallest class.
n_classes: integer, total number of equivalence classes.
n_violations: integer, number of classes below the threshold.
violating_classes: data.frame of class keys plus their .n sizes (empty data.frame when none).
summary: human-readable one-line summary.

Examples

df <- data.frame(
  age = c(25, 25, 25, 32, 32, 40),
  sex = c("F", "F", "F", "M", "M", "M")
)

# k = 2: the class {age=40, sex=M} has only 1 row -> VIOLATED.
res <- morie_k_anonymity_verify(df, c("age", "sex"), k = 2)
res$summary
#> [1] "k=2: VIOLATED (min class size=1; 1/3 classes below threshold)"
res$satisfies
#> [1] FALSE
res$violating_classes # the offending quasi-identifier combos
#>   age sex .n
#> 1  40   M  1

# Loosening to k = 1 always holds; the default k = 5 is stricter.
morie_k_anonymity_verify(df, c("age", "sex"), k = 1)$satisfies
#> [1] TRUE
morie_k_anonymity_verify(df, c("age", "sex"))$satisfies # k = 5
#> [1] FALSE

# A single quasi-identifier is fine too.
morie_k_anonymity_verify(df, "sex", k = 3)$min_class_size
#> [1] 3

# On real bundled data: are (year, arrest) cells 5-anonymous?
morie_k_anonymity_verify(complaint_sample,
  c("year", "arrest"),
  k = 5
)$summary
#> [1] "k=5: VIOLATED (min class size=1; 1/3 classes below threshold)"