Configure Discrete Perturbation

Prerequisites

To use perturbation, you must have:

  • R Keys in the unit records.
  • A perturbation table (PTable) file for each dataset. This file is in CSV format with the extension .pert

Module Properties

The Perturbation module has the following properties you can configure.

PropertyDescription
RKEY
Set this to true to use the R Keys in the unit records.
FREQ
Set this to true to perturb cell values based on the contribution count rather than the cross-tabulation (cell) value.
SmallN

An integer that controls how to lookup values for the perturbation table when the cell value being perturbed is larger than the width of the PTable. 

An important feature of perturbation is that all cell values get perturbed, even large values. The cell value determines which column in the PTable is used to look up the adjustment (i.e., if the cell value is 8, the perturbation adjustment would be selected from column 8). When the cell value is larger than the width of the PTable, the perturbation algorithm simply loops through the rightmost columns of the PTable (otherwise the PTable would need to have enough columns for any possible cell value). 

The SmallN  determines how many columns on the right of the PTable it should loop through.

Its value can be 10 or below. The default value is 10.

For example, if the SmallN  is 10 and the PTableSize is 30, then 

Cell Value Is...Lookup From Column...
3122
3223
......
3930
4021
4122
......
RULESET

Use this option to perturb other results:

  • Set this to the value "PERT()" (or omit the RULESET property altogether) for the default behaviour: discrete perturbation will apply to counts in the cross tabulation results.
  • Use the following optional parameters of PERT() to perturb another result set:
    • The first parameter determines whether to perturb measures. Set this to true (perturb measures) or false (do not perturb measures). This would usually be set to false when using discrete perturbation, as this is intended to perturb counts.
    • The second parameter identifies the destination for the perturbation calculation. If not specified this will be the cross tabulation results.
    • The third parameter identifies the source of the perturbation calculation. If not specified this will use the same value as the destination.
  • You can specify multiple RULESET options: separate each one with a | character.

For example:

method "Rule" perturbation addproperty RULESET "PERT()"
The default behaviour. Perturb counts in the cross tabulation results.
method "Rule" perturbation addproperty RULESET "PERT(true)"
Perturb measures in the cross tabulation results.
method "Rule" perturbation addproperty RULESET "PERT(true,RECORD_COUNT)"
Perturb the output from the record count plugin. See the example below for more details on this configuration.
method "Rule" perturbation addproperty RULESET "PERT()|PERT(true,RECORD_COUNT)"
Perturb the counts in the cross tabulation results and the output from the record count plugin (see the example below).
PTableSize
The number of columns in the perturbation table. The default value is 30.
BigN
An integer to be used as the modulo base when adding R Keys. Must not exceed 2^32 (4294967296). The default value is 4294967296.
ConfidentialityModule

Set this to true to indicate to SuperSERVER that this module applies confidentiality rules. When set to true SuperSERVER will block access to the Record View feature.

Message
A message to be displayed to users in the client.
PTable

The location of the perturbation file for this dataset.

If you do not set a value for the PTable property, then by default SuperSERVER expects this file to be saved in the same location as the SXV4 file, but with the extension .pert instead of .sxv4. For example, if the SXV4 file is C:\ProgramData\STR\SuperSERVER SA\databases\RetailBanking.sxv4 then the perturbation file is expected to be located at C:\ProgramData\STR\SuperSERVER SA\databases\RetailBanking.pert

If you want to use a different location for the file, then you can set the value of PTable to the location of the .pert file. You can either use an absolute path or a relative path (relative to the SuperSERVER program data directory, which is C:\ProgramData\STR\SuperSERVER SA if you installed to the default location).

Any backslashes in the path will need to be escaped with an additional backslash (forward slashes can also be used but do not need to be escaped). For example:

method "Rule" perturbation addproperty PTable "C:\\ProgramData\\STR\\SuperSERVER SA\\databases\\my-ptable.pert"

If the contents of the perturbation file are modified in any way, you must restart SuperSERVER in order for the change to take effect. This is for performance reasons (SuperSERVER caches the perturbation file so that it does not have to reload and parse it on every tabulation).

PropagateZeroes

Whether to propagate zeros between fact tables.

This setting is designed to counter a potential attack vector for perturbation in cases where it might be possible to use information from one fact table to infer that a value for a related fact table, which has been perturbed to zero, is not a true zero.

For example, consider a case where there is a household fact table and a people fact table describing the people within those households. An attacker might be able to create a table that counts households where a particular cell has one true record, representing a single household. The value of this cell would be perturbed to zero. However, if the attacker changes the table so that it counts people instead, and sees that there is now a value returned for that cell (because the number of people in that single household is large enough not to be perturbed to zero), then the attacker now knows that there is in fact at least one household record for that cell. 

Propagate zeros is designed to circumvent this attack by propagating the perturbed zero between fact tables. In this example, it would propagate the perturbed zero from the household level down to the people level. The table counting people would therefore also return a zero value, regardless of how many people there actually are in that household.

This setting also coordinates perturbation with measures: if a fact table count is perturbed to zero, then the measures for that fact table will also be perturbed to zero.

To apply zero propagation, use the following command:

method <method_id> perturbation addproperty PropagateZeroes {"All"|"Ancestor"|"Same"|"None"}

The available settings are:

AncestorPropagation only happens one way: from ancestor to descendant fact tables. For example, from the (parent) household fact table to the (child) people fact table.
AllPropagation happens both ways to all fact tables.
SamePropagation happens only from the count to the measures within the same fact table.
NoneNo propagation happens (default).

For example:

method "Rule" perturbation addproperty PropagateZeroes "Ancestor"
PropagateZeroesFieldValues

An optional setting that allows you to configure the propagate zeroes feature so that it only runs if specific fields or field values are in the table.

You can choose to specify:

  • An entire field, in which case propagate zeroes will apply if any value from that field is in the table; or
  • A field followed by a comma separated list of values from that field, in which case propagate zeroes will apply if any one of those specific values is in the table.

To apply conditional propagate zeroes, use the following commands: 

method <method_id> perturbation addproperty progagateZeroesFieldValues "<fact_table_id>__<field_id>"

method <method_id> perturbation addproperty progagateZeroesFieldValues "<display_name>"

method <method_id> perturbation addproperty progagateZeroesFieldValues "<fact_table_id>__<field_id>,<field_value_id>,<field_value_id>..."

method <method_id> perturbation addproperty progagateZeroesFieldValues "<display_name>,<field_value_display_name>,<field_value_display_name>..."

You can specify multiple fields, in which case propagate zeroes will apply if any one of those fields or the specified field values are in the table. If you want to list a large number of fields, it may be easier to use the PropagateZeroesFieldValuesFile  option instead, which allows you to use a text file to specify the list.

As shown above, you can either use display names or IDs when specifying the list. IDs are strongly recommended as it ensures that field values will be considered even if they are in group recodes.

You can obtain IDs from SuperADMIN using the cat  command:

cat <dataset_id> <field_name>

For example:

> cat bank Gender
[ XTAB Field : 'Gender' ]
    [ ID : 'SXV4__Retail_Banking__F_Customer__Gender_FLD' ]
    [ Value Set : 'SXV4__Retail_Banking__C_Gender' ]

In this example the fact table ID is F_Customer and the field ID is Gender . To configure propagate zeros to only apply if the Gender field is in the table, you would use a command similar to the following:

method "Rule" perturbation addproperty PropagateZeroesFieldValues "F_Customer__Gender"

When specifying field values, you can also use either display names or IDs. You can obtain the IDs in SuperADMIN as follows:

cat <dataset_id> <field_name> values

 For example: 

> cat bank 'Marital Status' values
[ Value : 'Single' (id:S) ]
 [ Value : 'Married' (id:M) ]
 [ Value : 'Divorced' (id:D) ]
 [ Value : 'Unknown' (id:U) ]
 [ Value : 'Not Applicable' (id:-1) ]

To configure propagate zeroes to only apply if Married or Divorced are in the table, you would use a command similar to the following:

method "Rule" perturbation addproperty PropagateZeroesFieldValues "F_Customer__Marital_Status,M,D"
PropagateZeroesFieldValuesFile

An optional setting that allows you to specify a CSV file containing a list of fields or field values where you want propagate zeroes to apply.

Fields and field values are specified in the same way as when using PropagateZeroesFieldValues .

method <method_id> perturbation addproperty progagateZeroesFieldValuesFile "<filename>"

Save your file to the SuperSERVER data directory (C:\ProgramData\STR\SuperSERVER SA).

For example:

method "Rule" perturbation addproperty PropagateZeroesFieldValuesFile "propagate-zeroes.csv"
propagate-zeroes.csv
method "Rule" perturbation addproperty PropagateZeroesFieldValues "F_Customer__Gender"
method "Rule" perturbation addproperty PropagateZeroesFieldValues "F_Customer__Marital_Status,M,D"
PropagateZeroesThreshold

The propagation threshold. Use the threshold to control whether a cell can be set to zero by zero propagation from a related level/record count:

method <method_id> perturbation addproperty PropagateZeroesThreshold "<number>"

If the record count of a cell is less than or equal to this threshold, then it can be set to zero by zero propagation.

For example, the following command ensures that cells with record counts of 5 or less can be set to zero:

method "Rule" perturbation addproperty PropagateZeroesThreshold "5"
QUANTILEVALIDATION
QUANTILEPTABLE
QUANTILECONFIG
The location of the configuration files for quantile perturbation. By default, these files should be in the same location as the SXV4 file, but you can use these properties to set an alternative location. See Quantiles and Ranges for more details.

Apply the Plugin

  1. Login to SuperADMIN and create a new method:

    > method addmethod perturbation_method

    This example sets the ID of the new method to perturbation_method. This ID will be used in all the following examples, although you can replace this with your preferred ID if you wish.

  2. Add the Perturbation Data Control plugin to the method:

    > method perturbation_method adddcplugin perturbation Perturbation

    This example sets the ID of the plugin within this method to perturbation. You can replace this with your preferred ID.

    The Perturbation at the end of this command is the library name for the perturbation module. This is case sensitive and must be specified exactly as shown here.

  3. Set the plugin properties:

    > method perturbation_method perturbation addproperty RKEY "true"
    > method perturbation_method perturbation addproperty FREQ "true"
    > method perturbation_method perturbation addproperty "SmallN" "10"
    > method perturbation_method perturbation addproperty "PTableSize" "30"
    > method perturbation_method perturbation addproperty "BigN" "4294967296"
    > method perturbation_method perturbation addproperty ConfidentialityModule "true"
    > method perturbation_method perturbation addproperty Message "Data has been perturbed"
  4. Assign the method to a dataset (in this example we are assigning the method to a dataset with the ID bank):

    > cat bank addmethod perturbation_method

    You can review the method details using the command cat <dataset_id> methods details <method_id>:

    > cat bank methods details perturbation_method
    [ Method : perturbation_method (id:perturbation_method) (type:mandatory) ]
        [ Common ]
        [ DCPlugin : Perturbation (id:perturbation) (priority:1) ]
            [ RKEY : true ]
            [ FREQ : true ]
            [ SmallN : 10 ]
            [ PTableSize : 30 ]
            [ BigN : 4294967296 ]
            [ ConfidentialityModule : true ]
            [ Message : Data has been perturbed ]

Perturbation with Weighted Datasets

If you have weighted datasets, then you must apply an additional data control module, Average_cellwgt, to your perturbation methods. This module effectively scales up the perturbed amount to account for the weighting.

The average cell weighting module calculates the unweighted cell value, applies perturbation to this, and then multiples the result by the average weight of the cell (calculated as the weighted value divided by the unweighted value):

(unweighted count + perturbation factor) * (weighted count / unweighted count)

This ensures that the effect of perturbation is scaled up appropriately to account for the weighting.

When using weighted datasets:

  • The average cell weight module must be added to the method after the perturbation module, as it uses the result of the perturbation as part of its calculation.
  • The FREQ property must be set to true.

The following is a complete example of perturbation with weighted datasets:

method addmethod weighted_perturbation_example

method weighted_perturbation_example adddcplugin weighted_perturbation Perturbation
method weighted_perturbation_example weighted_perturbation addproperty RKEY "true"
method weighted_perturbation_example weighted_perturbation addproperty "SmallN" "10"
method weighted_perturbation_example weighted_perturbation addproperty "PTableSize" "30"
method weighted_perturbation_example weighted_perturbation addproperty "BigN" "4294967296"
method weighted_perturbation_example weighted_perturbation addproperty ConfidentialityModule "true"
method weighted_perturbation_example weighted_perturbation addproperty Message "Data has been perturbed"

method weighted_perturbation_example adddcplugin Average_cellwgt Average_cellwgt

method weighted_perturbation_example common addproperty FREQ "true"