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Apply primary suppression

Source: R/primarySuppression.R
primarySuppression.Rd

primarySuppression() identifies and suppresses primary sensitive table cells within sdcProblem objects based on specified rules.

Usage

primarySuppression(object, type, ...)

Arguments

object

an sdcProblem object.

type

character string defining the primary suppression rule. Allowed values are:

  • "freq": apply frequency rule (uses maxN and allowZeros).

  • "nk": apply nk-dominance rule (uses n and k).

  • "p": apply p-percent rule (uses p).

  • "pq": apply pq-rule (uses p and q).

...

parameters for the selected primary suppression rule:

  • maxN: scalar integerish; cells with counts <= maxN are suppressed. Defaults to 3.

  • allowZeros: scalar logical; if TRUE, empty cells (frequency 0) are considered sensitive. Defaults to FALSE. Empty cells not flagged as sensitive are marked as z (published, but not used for secondary suppression).

  • p: scalar integerish; threshold parameter for p-percent or pq-rules. Defaults to 80.

  • q: scalar numeric; threshold parameter for pq-rule. Defaults to 50.

  • n: scalar integerish; parameter n for the nk-dominance rule. Defaults to 2.

  • k: scalar integerish; parameter k for the nk-dominance rule. Defaults to 85.

  • numVarName: scalar character; the name of the numerical variable used for dominance-based rules. This is mandatory for nk, p, and pq rules.

Value

an sdcProblem object.

Details

Currently, the frequency rule, nk-dominance rule, p-percent rule and pq-rule are supported.

Note: Since version 0.29, dominance-based rules ("p", "pq", or "nk") require the identification of the numerical variable by name using the numVarName argument. Identification by index is no longer supported.

Note

The “nk-dominance, p`-percent, and `pq`-rules require microdata as input to makeProblem().

Cell Status Codes

When an object of class sdcProblem is created, every cell is assigned an internal anonymization state. These codes track the lifecycle of a cell throughout the suppression process:

  • "s" ("Publishable"): The cell is safe and can be published (default).

  • "z"("Forced Publishable"): The cell must not be suppressed under any circumstances.

  • "u" (*"Primary Suppressed"): The cell is identified as sensitive and requires protection (typically assigned via primarySuppression()).

  • "x" ("Secondary Suppressed"): The cell is suppressed to protect primary sensitive cells (typically assigned via protectTable()).

  • "w" ("Extension Cell"): The cell exists in the object but will never be published. It is treated as a suppressed cell by internal algorithms. This is useful if it is known in advance that specific codes of a hierarchy will be excluded from publication.

Initially in makeProblem(), cells are coded as "s" or "z". Their status transitions to "u" or "x" as suppression algorithms are applied.

While setInfo() or change_cellstatus() allow for manual state modifications, primarySuppression() automatically identifies primary sensitive cells and assigns state "u". In protectTable(), additional cells are identified and set to "x" to ensure all primary sensitive cells are adequately protected.

Author

Bernhard Meindl bernhard.meindl@statistik.gv.at

Examples

# load micro data and create a problem instance
utils::data("microdata1", package = "sdcTable")
p <- sdc_testproblem(with_supps = FALSE)

# apply frequency rule
p1 <- primarySuppression(
  object = p,
  type = "freq",
  maxN = 2
)

# apply p-percent rule (requires specifying a numeric variable)
p2 <- primarySuppression(
  object = p,
  type = "p",
  p = 30,
  numVarName = "val"
)

# compare results
data.frame(
  p1_sdc = getInfo(p1, type = "sdcStatus"),
  p2_sdc = getInfo(p2, type = "sdcStatus")
)
#>    p1_sdc p2_sdc
#> 1       s      s
#> 2       s      s
#> 3       s      s
#> 4       s      s
#> 5       s      s
#> 6       u      u
#> 7       s      s
#> 8       s      s
#> 9       s      s
#> 10      s      s
#> 11      s      s
#> 12      s      s
#> 13      s      s
#> 14      s      u
#> 15      s      s