Class: Google::Cloud::Dlp::V2::PrivacyMetric

Inherits:
Object
  • Object
show all
Extended by:
Protobuf::MessageExts::ClassMethods
Includes:
Protobuf::MessageExts
Defined in:
proto_docs/google/privacy/dlp/v2/dlp.rb

Overview

Privacy metric to compute for reidentification risk analysis.

Defined Under Namespace

Classes: CategoricalStatsConfig, DeltaPresenceEstimationConfig, KAnonymityConfig, KMapEstimationConfig, LDiversityConfig, NumericalStatsConfig

Instance Attribute Summary collapse

Instance Attribute Details

#categorical_stats_config ⇒ ::Google::Cloud::Dlp::V2::PrivacyMetric::CategoricalStatsConfig

Returns Categorical stats

Note: The following fields are mutually exclusive: categorical_stats_config, numerical_stats_config, k_anonymity_config, l_diversity_config, k_map_estimation_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns:

  • (::Google::Cloud::Dlp::V2::PrivacyMetric::CategoricalStatsConfig) —

    Categorical stats

    Note: The following fields are mutually exclusive: categorical_stats_config, numerical_stats_config, k_anonymity_config, l_diversity_config, k_map_estimation_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.



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# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 2030

class PrivacyMetric
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Compute numerical stats over an individual column, including
  # min, max, and quantiles.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute numerical stats on. Supported types are
  #     integer, float, date, datetime, timestamp, time.
  class NumericalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Compute numerical stats over an individual column, including
  # number of distinct values and value count distribution.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute categorical stats on. All column types are
  #     supported except for arrays and structs. However, it may be more
  #     informative to use NumericalStats when the field type is supported,
  #     depending on the data.
  class CategoricalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # k-anonymity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of fields to compute k-anonymity over. When multiple fields are
  #     specified, they are considered a single composite key. Structs and
  #     repeated data types are not supported; however, nested fields are
  #     supported so long as they are not structs themselves or nested within
  #     a repeated field.
  # @!attribute [rw] entity_id
  #   @return [::Google::Cloud::Dlp::V2::EntityId]
  #     Message indicating that multiple rows might be associated to a
  #     single individual. If the same entity_id is associated to multiple
  #     quasi-identifier tuples over distinct rows, we consider the entire
  #     collection of tuples as the composite quasi-identifier. This collection
  #     is a multiset: the order in which the different tuples appear in the
  #     dataset is ignored, but their frequency is taken into account.
  #
  #     Important note: a maximum of 1000 rows can be associated to a single
  #     entity ID. If more rows are associated with the same entity ID, some
  #     might be ignored.
  class KAnonymityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # l-diversity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of quasi-identifiers indicating how equivalence classes are
  #     defined for the l-diversity computation. When multiple fields are
  #     specified, they are considered a single composite key.
  # @!attribute [rw] sensitive_attribute
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Sensitive field for computing the l-value.
  class LDiversityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Reidentifiability metric. This corresponds to a risk model similar to what
  # is called "journalist risk" in the literature, except the attack dataset is
  # statistically modeled instead of being perfectly known. This can be done
  # using publicly available data (like the US Census), or using a custom
  # statistical model (indicated as one or several BigQuery tables), or by
  # extrapolating from the distribution of values in the input dataset.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::TaggedField>]
  #     Required. Fields considered to be quasi-identifiers. No two columns can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers column must appear in exactly one column
  #     of one auxiliary table.
  class KMapEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # A column with a semantic tag attached.
    # @!attribute [rw] field
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. Identifies the column.
    # @!attribute [rw] info_type
    #   @return [::Google::Cloud::Dlp::V2::InfoType]
    #     A column can be tagged with a InfoType to use the relevant public
    #     dataset as a statistical model of population, if available. We
    #     currently support US ZIP codes, region codes, ages and genders.
    #     To programmatically obtain the list of supported InfoTypes, use
    #     ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
    #
    #     Note: The following fields are mutually exclusive: `info_type`, `custom_tag`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] custom_tag
    #   @return [::String]
    #     A column can be tagged with a custom tag. In this case, the user must
    #     indicate an auxiliary table that contains statistical information on
    #     the possible values of this column.
    #
    #     Note: The following fields are mutually exclusive: `custom_tag`, `info_type`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] inferred
    #   @return [::Google::Protobuf::Empty]
    #     If no semantic tag is indicated, we infer the statistical model from
    #     the distribution of values in the input data
    #
    #     Note: The following fields are mutually exclusive: `inferred`, `info_type`, `custom_tag`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    class TaggedField
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # An auxiliary table contains statistical information on the relative
    # frequency of different quasi-identifiers values. It has one or several
    # quasi-identifiers columns, and one column that indicates the relative
    # frequency of each quasi-identifier tuple.
    # If a tuple is present in the data but not in the auxiliary table, the
    # corresponding relative frequency is assumed to be zero (and thus, the
    # tuple is highly reidentifiable).
    # @!attribute [rw] table
    #   @return [::Google::Cloud::Dlp::V2::BigQueryTable]
    #     Required. Auxiliary table location.
    # @!attribute [rw] quasi_ids
    #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable::QuasiIdField>]
    #     Required. Quasi-identifier columns.
    # @!attribute [rw] relative_frequency
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. The relative frequency column must contain a floating-point
    #     number between 0 and 1 (inclusive). Null values are assumed to be zero.
    class AuxiliaryTable
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # A quasi-identifier column has a custom_tag, used to know which column
      # in the data corresponds to which column in the statistical model.
      # @!attribute [rw] field
      #   @return [::Google::Cloud::Dlp::V2::FieldId]
      #     Identifies the column.
      # @!attribute [rw] custom_tag
      #   @return [::String]
      #     A auxiliary field.
      class QuasiIdField
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end

  # δ-presence metric, used to estimate how likely it is for an attacker to
  # figure out that one given individual appears in a de-identified dataset.
  # Similarly to the k-map metric, we cannot compute δ-presence exactly without
  # knowing the attack dataset, so we use a statistical model instead.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::QuasiId>]
  #     Required. Fields considered to be quasi-identifiers. No two fields can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::StatisticalTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers field must appear in exactly one
  #     field of one auxiliary table.
  class DeltaPresenceEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#delta_presence_estimation_config ⇒ ::Google::Cloud::Dlp::V2::PrivacyMetric::DeltaPresenceEstimationConfig

Returns delta-presence

Note: The following fields are mutually exclusive: delta_presence_estimation_config, numerical_stats_config, categorical_stats_config, k_anonymity_config, l_diversity_config, k_map_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns:

  • (::Google::Cloud::Dlp::V2::PrivacyMetric::DeltaPresenceEstimationConfig) —

    delta-presence

    Note: The following fields are mutually exclusive: delta_presence_estimation_config, numerical_stats_config, categorical_stats_config, k_anonymity_config, l_diversity_config, k_map_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.



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# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 2030

class PrivacyMetric
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Compute numerical stats over an individual column, including
  # min, max, and quantiles.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute numerical stats on. Supported types are
  #     integer, float, date, datetime, timestamp, time.
  class NumericalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Compute numerical stats over an individual column, including
  # number of distinct values and value count distribution.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute categorical stats on. All column types are
  #     supported except for arrays and structs. However, it may be more
  #     informative to use NumericalStats when the field type is supported,
  #     depending on the data.
  class CategoricalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # k-anonymity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of fields to compute k-anonymity over. When multiple fields are
  #     specified, they are considered a single composite key. Structs and
  #     repeated data types are not supported; however, nested fields are
  #     supported so long as they are not structs themselves or nested within
  #     a repeated field.
  # @!attribute [rw] entity_id
  #   @return [::Google::Cloud::Dlp::V2::EntityId]
  #     Message indicating that multiple rows might be associated to a
  #     single individual. If the same entity_id is associated to multiple
  #     quasi-identifier tuples over distinct rows, we consider the entire
  #     collection of tuples as the composite quasi-identifier. This collection
  #     is a multiset: the order in which the different tuples appear in the
  #     dataset is ignored, but their frequency is taken into account.
  #
  #     Important note: a maximum of 1000 rows can be associated to a single
  #     entity ID. If more rows are associated with the same entity ID, some
  #     might be ignored.
  class KAnonymityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # l-diversity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of quasi-identifiers indicating how equivalence classes are
  #     defined for the l-diversity computation. When multiple fields are
  #     specified, they are considered a single composite key.
  # @!attribute [rw] sensitive_attribute
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Sensitive field for computing the l-value.
  class LDiversityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Reidentifiability metric. This corresponds to a risk model similar to what
  # is called "journalist risk" in the literature, except the attack dataset is
  # statistically modeled instead of being perfectly known. This can be done
  # using publicly available data (like the US Census), or using a custom
  # statistical model (indicated as one or several BigQuery tables), or by
  # extrapolating from the distribution of values in the input dataset.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::TaggedField>]
  #     Required. Fields considered to be quasi-identifiers. No two columns can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers column must appear in exactly one column
  #     of one auxiliary table.
  class KMapEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # A column with a semantic tag attached.
    # @!attribute [rw] field
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. Identifies the column.
    # @!attribute [rw] info_type
    #   @return [::Google::Cloud::Dlp::V2::InfoType]
    #     A column can be tagged with a InfoType to use the relevant public
    #     dataset as a statistical model of population, if available. We
    #     currently support US ZIP codes, region codes, ages and genders.
    #     To programmatically obtain the list of supported InfoTypes, use
    #     ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
    #
    #     Note: The following fields are mutually exclusive: `info_type`, `custom_tag`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] custom_tag
    #   @return [::String]
    #     A column can be tagged with a custom tag. In this case, the user must
    #     indicate an auxiliary table that contains statistical information on
    #     the possible values of this column.
    #
    #     Note: The following fields are mutually exclusive: `custom_tag`, `info_type`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] inferred
    #   @return [::Google::Protobuf::Empty]
    #     If no semantic tag is indicated, we infer the statistical model from
    #     the distribution of values in the input data
    #
    #     Note: The following fields are mutually exclusive: `inferred`, `info_type`, `custom_tag`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    class TaggedField
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # An auxiliary table contains statistical information on the relative
    # frequency of different quasi-identifiers values. It has one or several
    # quasi-identifiers columns, and one column that indicates the relative
    # frequency of each quasi-identifier tuple.
    # If a tuple is present in the data but not in the auxiliary table, the
    # corresponding relative frequency is assumed to be zero (and thus, the
    # tuple is highly reidentifiable).
    # @!attribute [rw] table
    #   @return [::Google::Cloud::Dlp::V2::BigQueryTable]
    #     Required. Auxiliary table location.
    # @!attribute [rw] quasi_ids
    #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable::QuasiIdField>]
    #     Required. Quasi-identifier columns.
    # @!attribute [rw] relative_frequency
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. The relative frequency column must contain a floating-point
    #     number between 0 and 1 (inclusive). Null values are assumed to be zero.
    class AuxiliaryTable
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # A quasi-identifier column has a custom_tag, used to know which column
      # in the data corresponds to which column in the statistical model.
      # @!attribute [rw] field
      #   @return [::Google::Cloud::Dlp::V2::FieldId]
      #     Identifies the column.
      # @!attribute [rw] custom_tag
      #   @return [::String]
      #     A auxiliary field.
      class QuasiIdField
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end

  # δ-presence metric, used to estimate how likely it is for an attacker to
  # figure out that one given individual appears in a de-identified dataset.
  # Similarly to the k-map metric, we cannot compute δ-presence exactly without
  # knowing the attack dataset, so we use a statistical model instead.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::QuasiId>]
  #     Required. Fields considered to be quasi-identifiers. No two fields can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::StatisticalTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers field must appear in exactly one
  #     field of one auxiliary table.
  class DeltaPresenceEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#k_anonymity_config ⇒ ::Google::Cloud::Dlp::V2::PrivacyMetric::KAnonymityConfig

Returns K-anonymity

Note: The following fields are mutually exclusive: k_anonymity_config, numerical_stats_config, categorical_stats_config, l_diversity_config, k_map_estimation_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns:

  • (::Google::Cloud::Dlp::V2::PrivacyMetric::KAnonymityConfig) —

    K-anonymity

    Note: The following fields are mutually exclusive: k_anonymity_config, numerical_stats_config, categorical_stats_config, l_diversity_config, k_map_estimation_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.



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# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 2030

class PrivacyMetric
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Compute numerical stats over an individual column, including
  # min, max, and quantiles.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute numerical stats on. Supported types are
  #     integer, float, date, datetime, timestamp, time.
  class NumericalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Compute numerical stats over an individual column, including
  # number of distinct values and value count distribution.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute categorical stats on. All column types are
  #     supported except for arrays and structs. However, it may be more
  #     informative to use NumericalStats when the field type is supported,
  #     depending on the data.
  class CategoricalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # k-anonymity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of fields to compute k-anonymity over. When multiple fields are
  #     specified, they are considered a single composite key. Structs and
  #     repeated data types are not supported; however, nested fields are
  #     supported so long as they are not structs themselves or nested within
  #     a repeated field.
  # @!attribute [rw] entity_id
  #   @return [::Google::Cloud::Dlp::V2::EntityId]
  #     Message indicating that multiple rows might be associated to a
  #     single individual. If the same entity_id is associated to multiple
  #     quasi-identifier tuples over distinct rows, we consider the entire
  #     collection of tuples as the composite quasi-identifier. This collection
  #     is a multiset: the order in which the different tuples appear in the
  #     dataset is ignored, but their frequency is taken into account.
  #
  #     Important note: a maximum of 1000 rows can be associated to a single
  #     entity ID. If more rows are associated with the same entity ID, some
  #     might be ignored.
  class KAnonymityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # l-diversity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of quasi-identifiers indicating how equivalence classes are
  #     defined for the l-diversity computation. When multiple fields are
  #     specified, they are considered a single composite key.
  # @!attribute [rw] sensitive_attribute
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Sensitive field for computing the l-value.
  class LDiversityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Reidentifiability metric. This corresponds to a risk model similar to what
  # is called "journalist risk" in the literature, except the attack dataset is
  # statistically modeled instead of being perfectly known. This can be done
  # using publicly available data (like the US Census), or using a custom
  # statistical model (indicated as one or several BigQuery tables), or by
  # extrapolating from the distribution of values in the input dataset.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::TaggedField>]
  #     Required. Fields considered to be quasi-identifiers. No two columns can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers column must appear in exactly one column
  #     of one auxiliary table.
  class KMapEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # A column with a semantic tag attached.
    # @!attribute [rw] field
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. Identifies the column.
    # @!attribute [rw] info_type
    #   @return [::Google::Cloud::Dlp::V2::InfoType]
    #     A column can be tagged with a InfoType to use the relevant public
    #     dataset as a statistical model of population, if available. We
    #     currently support US ZIP codes, region codes, ages and genders.
    #     To programmatically obtain the list of supported InfoTypes, use
    #     ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
    #
    #     Note: The following fields are mutually exclusive: `info_type`, `custom_tag`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] custom_tag
    #   @return [::String]
    #     A column can be tagged with a custom tag. In this case, the user must
    #     indicate an auxiliary table that contains statistical information on
    #     the possible values of this column.
    #
    #     Note: The following fields are mutually exclusive: `custom_tag`, `info_type`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] inferred
    #   @return [::Google::Protobuf::Empty]
    #     If no semantic tag is indicated, we infer the statistical model from
    #     the distribution of values in the input data
    #
    #     Note: The following fields are mutually exclusive: `inferred`, `info_type`, `custom_tag`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    class TaggedField
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # An auxiliary table contains statistical information on the relative
    # frequency of different quasi-identifiers values. It has one or several
    # quasi-identifiers columns, and one column that indicates the relative
    # frequency of each quasi-identifier tuple.
    # If a tuple is present in the data but not in the auxiliary table, the
    # corresponding relative frequency is assumed to be zero (and thus, the
    # tuple is highly reidentifiable).
    # @!attribute [rw] table
    #   @return [::Google::Cloud::Dlp::V2::BigQueryTable]
    #     Required. Auxiliary table location.
    # @!attribute [rw] quasi_ids
    #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable::QuasiIdField>]
    #     Required. Quasi-identifier columns.
    # @!attribute [rw] relative_frequency
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. The relative frequency column must contain a floating-point
    #     number between 0 and 1 (inclusive). Null values are assumed to be zero.
    class AuxiliaryTable
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # A quasi-identifier column has a custom_tag, used to know which column
      # in the data corresponds to which column in the statistical model.
      # @!attribute [rw] field
      #   @return [::Google::Cloud::Dlp::V2::FieldId]
      #     Identifies the column.
      # @!attribute [rw] custom_tag
      #   @return [::String]
      #     A auxiliary field.
      class QuasiIdField
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end

  # δ-presence metric, used to estimate how likely it is for an attacker to
  # figure out that one given individual appears in a de-identified dataset.
  # Similarly to the k-map metric, we cannot compute δ-presence exactly without
  # knowing the attack dataset, so we use a statistical model instead.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::QuasiId>]
  #     Required. Fields considered to be quasi-identifiers. No two fields can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::StatisticalTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers field must appear in exactly one
  #     field of one auxiliary table.
  class DeltaPresenceEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#k_map_estimation_config ⇒ ::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig

Returns k-map

Note: The following fields are mutually exclusive: k_map_estimation_config, numerical_stats_config, categorical_stats_config, k_anonymity_config, l_diversity_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns:

  • (::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig) —

    k-map

    Note: The following fields are mutually exclusive: k_map_estimation_config, numerical_stats_config, categorical_stats_config, k_anonymity_config, l_diversity_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.



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# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 2030

class PrivacyMetric
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Compute numerical stats over an individual column, including
  # min, max, and quantiles.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute numerical stats on. Supported types are
  #     integer, float, date, datetime, timestamp, time.
  class NumericalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Compute numerical stats over an individual column, including
  # number of distinct values and value count distribution.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute categorical stats on. All column types are
  #     supported except for arrays and structs. However, it may be more
  #     informative to use NumericalStats when the field type is supported,
  #     depending on the data.
  class CategoricalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # k-anonymity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of fields to compute k-anonymity over. When multiple fields are
  #     specified, they are considered a single composite key. Structs and
  #     repeated data types are not supported; however, nested fields are
  #     supported so long as they are not structs themselves or nested within
  #     a repeated field.
  # @!attribute [rw] entity_id
  #   @return [::Google::Cloud::Dlp::V2::EntityId]
  #     Message indicating that multiple rows might be associated to a
  #     single individual. If the same entity_id is associated to multiple
  #     quasi-identifier tuples over distinct rows, we consider the entire
  #     collection of tuples as the composite quasi-identifier. This collection
  #     is a multiset: the order in which the different tuples appear in the
  #     dataset is ignored, but their frequency is taken into account.
  #
  #     Important note: a maximum of 1000 rows can be associated to a single
  #     entity ID. If more rows are associated with the same entity ID, some
  #     might be ignored.
  class KAnonymityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # l-diversity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of quasi-identifiers indicating how equivalence classes are
  #     defined for the l-diversity computation. When multiple fields are
  #     specified, they are considered a single composite key.
  # @!attribute [rw] sensitive_attribute
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Sensitive field for computing the l-value.
  class LDiversityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Reidentifiability metric. This corresponds to a risk model similar to what
  # is called "journalist risk" in the literature, except the attack dataset is
  # statistically modeled instead of being perfectly known. This can be done
  # using publicly available data (like the US Census), or using a custom
  # statistical model (indicated as one or several BigQuery tables), or by
  # extrapolating from the distribution of values in the input dataset.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::TaggedField>]
  #     Required. Fields considered to be quasi-identifiers. No two columns can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers column must appear in exactly one column
  #     of one auxiliary table.
  class KMapEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # A column with a semantic tag attached.
    # @!attribute [rw] field
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. Identifies the column.
    # @!attribute [rw] info_type
    #   @return [::Google::Cloud::Dlp::V2::InfoType]
    #     A column can be tagged with a InfoType to use the relevant public
    #     dataset as a statistical model of population, if available. We
    #     currently support US ZIP codes, region codes, ages and genders.
    #     To programmatically obtain the list of supported InfoTypes, use
    #     ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
    #
    #     Note: The following fields are mutually exclusive: `info_type`, `custom_tag`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] custom_tag
    #   @return [::String]
    #     A column can be tagged with a custom tag. In this case, the user must
    #     indicate an auxiliary table that contains statistical information on
    #     the possible values of this column.
    #
    #     Note: The following fields are mutually exclusive: `custom_tag`, `info_type`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] inferred
    #   @return [::Google::Protobuf::Empty]
    #     If no semantic tag is indicated, we infer the statistical model from
    #     the distribution of values in the input data
    #
    #     Note: The following fields are mutually exclusive: `inferred`, `info_type`, `custom_tag`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    class TaggedField
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # An auxiliary table contains statistical information on the relative
    # frequency of different quasi-identifiers values. It has one or several
    # quasi-identifiers columns, and one column that indicates the relative
    # frequency of each quasi-identifier tuple.
    # If a tuple is present in the data but not in the auxiliary table, the
    # corresponding relative frequency is assumed to be zero (and thus, the
    # tuple is highly reidentifiable).
    # @!attribute [rw] table
    #   @return [::Google::Cloud::Dlp::V2::BigQueryTable]
    #     Required. Auxiliary table location.
    # @!attribute [rw] quasi_ids
    #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable::QuasiIdField>]
    #     Required. Quasi-identifier columns.
    # @!attribute [rw] relative_frequency
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. The relative frequency column must contain a floating-point
    #     number between 0 and 1 (inclusive). Null values are assumed to be zero.
    class AuxiliaryTable
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # A quasi-identifier column has a custom_tag, used to know which column
      # in the data corresponds to which column in the statistical model.
      # @!attribute [rw] field
      #   @return [::Google::Cloud::Dlp::V2::FieldId]
      #     Identifies the column.
      # @!attribute [rw] custom_tag
      #   @return [::String]
      #     A auxiliary field.
      class QuasiIdField
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end

  # δ-presence metric, used to estimate how likely it is for an attacker to
  # figure out that one given individual appears in a de-identified dataset.
  # Similarly to the k-map metric, we cannot compute δ-presence exactly without
  # knowing the attack dataset, so we use a statistical model instead.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::QuasiId>]
  #     Required. Fields considered to be quasi-identifiers. No two fields can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::StatisticalTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers field must appear in exactly one
  #     field of one auxiliary table.
  class DeltaPresenceEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#l_diversity_config ⇒ ::Google::Cloud::Dlp::V2::PrivacyMetric::LDiversityConfig

Returns l-diversity

Note: The following fields are mutually exclusive: l_diversity_config, numerical_stats_config, categorical_stats_config, k_anonymity_config, k_map_estimation_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns:

  • (::Google::Cloud::Dlp::V2::PrivacyMetric::LDiversityConfig) —

    l-diversity

    Note: The following fields are mutually exclusive: l_diversity_config, numerical_stats_config, categorical_stats_config, k_anonymity_config, k_map_estimation_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.



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# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 2030

class PrivacyMetric
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Compute numerical stats over an individual column, including
  # min, max, and quantiles.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute numerical stats on. Supported types are
  #     integer, float, date, datetime, timestamp, time.
  class NumericalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Compute numerical stats over an individual column, including
  # number of distinct values and value count distribution.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute categorical stats on. All column types are
  #     supported except for arrays and structs. However, it may be more
  #     informative to use NumericalStats when the field type is supported,
  #     depending on the data.
  class CategoricalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # k-anonymity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of fields to compute k-anonymity over. When multiple fields are
  #     specified, they are considered a single composite key. Structs and
  #     repeated data types are not supported; however, nested fields are
  #     supported so long as they are not structs themselves or nested within
  #     a repeated field.
  # @!attribute [rw] entity_id
  #   @return [::Google::Cloud::Dlp::V2::EntityId]
  #     Message indicating that multiple rows might be associated to a
  #     single individual. If the same entity_id is associated to multiple
  #     quasi-identifier tuples over distinct rows, we consider the entire
  #     collection of tuples as the composite quasi-identifier. This collection
  #     is a multiset: the order in which the different tuples appear in the
  #     dataset is ignored, but their frequency is taken into account.
  #
  #     Important note: a maximum of 1000 rows can be associated to a single
  #     entity ID. If more rows are associated with the same entity ID, some
  #     might be ignored.
  class KAnonymityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # l-diversity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of quasi-identifiers indicating how equivalence classes are
  #     defined for the l-diversity computation. When multiple fields are
  #     specified, they are considered a single composite key.
  # @!attribute [rw] sensitive_attribute
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Sensitive field for computing the l-value.
  class LDiversityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Reidentifiability metric. This corresponds to a risk model similar to what
  # is called "journalist risk" in the literature, except the attack dataset is
  # statistically modeled instead of being perfectly known. This can be done
  # using publicly available data (like the US Census), or using a custom
  # statistical model (indicated as one or several BigQuery tables), or by
  # extrapolating from the distribution of values in the input dataset.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::TaggedField>]
  #     Required. Fields considered to be quasi-identifiers. No two columns can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers column must appear in exactly one column
  #     of one auxiliary table.
  class KMapEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # A column with a semantic tag attached.
    # @!attribute [rw] field
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. Identifies the column.
    # @!attribute [rw] info_type
    #   @return [::Google::Cloud::Dlp::V2::InfoType]
    #     A column can be tagged with a InfoType to use the relevant public
    #     dataset as a statistical model of population, if available. We
    #     currently support US ZIP codes, region codes, ages and genders.
    #     To programmatically obtain the list of supported InfoTypes, use
    #     ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
    #
    #     Note: The following fields are mutually exclusive: `info_type`, `custom_tag`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] custom_tag
    #   @return [::String]
    #     A column can be tagged with a custom tag. In this case, the user must
    #     indicate an auxiliary table that contains statistical information on
    #     the possible values of this column.
    #
    #     Note: The following fields are mutually exclusive: `custom_tag`, `info_type`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] inferred
    #   @return [::Google::Protobuf::Empty]
    #     If no semantic tag is indicated, we infer the statistical model from
    #     the distribution of values in the input data
    #
    #     Note: The following fields are mutually exclusive: `inferred`, `info_type`, `custom_tag`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    class TaggedField
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # An auxiliary table contains statistical information on the relative
    # frequency of different quasi-identifiers values. It has one or several
    # quasi-identifiers columns, and one column that indicates the relative
    # frequency of each quasi-identifier tuple.
    # If a tuple is present in the data but not in the auxiliary table, the
    # corresponding relative frequency is assumed to be zero (and thus, the
    # tuple is highly reidentifiable).
    # @!attribute [rw] table
    #   @return [::Google::Cloud::Dlp::V2::BigQueryTable]
    #     Required. Auxiliary table location.
    # @!attribute [rw] quasi_ids
    #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable::QuasiIdField>]
    #     Required. Quasi-identifier columns.
    # @!attribute [rw] relative_frequency
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. The relative frequency column must contain a floating-point
    #     number between 0 and 1 (inclusive). Null values are assumed to be zero.
    class AuxiliaryTable
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # A quasi-identifier column has a custom_tag, used to know which column
      # in the data corresponds to which column in the statistical model.
      # @!attribute [rw] field
      #   @return [::Google::Cloud::Dlp::V2::FieldId]
      #     Identifies the column.
      # @!attribute [rw] custom_tag
      #   @return [::String]
      #     A auxiliary field.
      class QuasiIdField
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end

  # δ-presence metric, used to estimate how likely it is for an attacker to
  # figure out that one given individual appears in a de-identified dataset.
  # Similarly to the k-map metric, we cannot compute δ-presence exactly without
  # knowing the attack dataset, so we use a statistical model instead.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::QuasiId>]
  #     Required. Fields considered to be quasi-identifiers. No two fields can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::StatisticalTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers field must appear in exactly one
  #     field of one auxiliary table.
  class DeltaPresenceEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#numerical_stats_config ⇒ ::Google::Cloud::Dlp::V2::PrivacyMetric::NumericalStatsConfig

Returns Numerical stats

Note: The following fields are mutually exclusive: numerical_stats_config, categorical_stats_config, k_anonymity_config, l_diversity_config, k_map_estimation_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns:

  • (::Google::Cloud::Dlp::V2::PrivacyMetric::NumericalStatsConfig) —

    Numerical stats

    Note: The following fields are mutually exclusive: numerical_stats_config, categorical_stats_config, k_anonymity_config, l_diversity_config, k_map_estimation_config, delta_presence_estimation_config. If a field in that set is populated, all other fields in the set will automatically be cleared.



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# File 'proto_docs/google/privacy/dlp/v2/dlp.rb', line 2030

class PrivacyMetric
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Compute numerical stats over an individual column, including
  # min, max, and quantiles.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute numerical stats on. Supported types are
  #     integer, float, date, datetime, timestamp, time.
  class NumericalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Compute numerical stats over an individual column, including
  # number of distinct values and value count distribution.
  # @!attribute [rw] field
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Field to compute categorical stats on. All column types are
  #     supported except for arrays and structs. However, it may be more
  #     informative to use NumericalStats when the field type is supported,
  #     depending on the data.
  class CategoricalStatsConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # k-anonymity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of fields to compute k-anonymity over. When multiple fields are
  #     specified, they are considered a single composite key. Structs and
  #     repeated data types are not supported; however, nested fields are
  #     supported so long as they are not structs themselves or nested within
  #     a repeated field.
  # @!attribute [rw] entity_id
  #   @return [::Google::Cloud::Dlp::V2::EntityId]
  #     Message indicating that multiple rows might be associated to a
  #     single individual. If the same entity_id is associated to multiple
  #     quasi-identifier tuples over distinct rows, we consider the entire
  #     collection of tuples as the composite quasi-identifier. This collection
  #     is a multiset: the order in which the different tuples appear in the
  #     dataset is ignored, but their frequency is taken into account.
  #
  #     Important note: a maximum of 1000 rows can be associated to a single
  #     entity ID. If more rows are associated with the same entity ID, some
  #     might be ignored.
  class KAnonymityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # l-diversity metric, used for analysis of reidentification risk.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::FieldId>]
  #     Set of quasi-identifiers indicating how equivalence classes are
  #     defined for the l-diversity computation. When multiple fields are
  #     specified, they are considered a single composite key.
  # @!attribute [rw] sensitive_attribute
  #   @return [::Google::Cloud::Dlp::V2::FieldId]
  #     Sensitive field for computing the l-value.
  class LDiversityConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end

  # Reidentifiability metric. This corresponds to a risk model similar to what
  # is called "journalist risk" in the literature, except the attack dataset is
  # statistically modeled instead of being perfectly known. This can be done
  # using publicly available data (like the US Census), or using a custom
  # statistical model (indicated as one or several BigQuery tables), or by
  # extrapolating from the distribution of values in the input dataset.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::TaggedField>]
  #     Required. Fields considered to be quasi-identifiers. No two columns can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers column must appear in exactly one column
  #     of one auxiliary table.
  class KMapEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # A column with a semantic tag attached.
    # @!attribute [rw] field
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. Identifies the column.
    # @!attribute [rw] info_type
    #   @return [::Google::Cloud::Dlp::V2::InfoType]
    #     A column can be tagged with a InfoType to use the relevant public
    #     dataset as a statistical model of population, if available. We
    #     currently support US ZIP codes, region codes, ages and genders.
    #     To programmatically obtain the list of supported InfoTypes, use
    #     ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
    #
    #     Note: The following fields are mutually exclusive: `info_type`, `custom_tag`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] custom_tag
    #   @return [::String]
    #     A column can be tagged with a custom tag. In this case, the user must
    #     indicate an auxiliary table that contains statistical information on
    #     the possible values of this column.
    #
    #     Note: The following fields are mutually exclusive: `custom_tag`, `info_type`, `inferred`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    # @!attribute [rw] inferred
    #   @return [::Google::Protobuf::Empty]
    #     If no semantic tag is indicated, we infer the statistical model from
    #     the distribution of values in the input data
    #
    #     Note: The following fields are mutually exclusive: `inferred`, `info_type`, `custom_tag`. If a field in that set is populated, all other fields in the set will automatically be cleared.
    class TaggedField
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods
    end

    # An auxiliary table contains statistical information on the relative
    # frequency of different quasi-identifiers values. It has one or several
    # quasi-identifiers columns, and one column that indicates the relative
    # frequency of each quasi-identifier tuple.
    # If a tuple is present in the data but not in the auxiliary table, the
    # corresponding relative frequency is assumed to be zero (and thus, the
    # tuple is highly reidentifiable).
    # @!attribute [rw] table
    #   @return [::Google::Cloud::Dlp::V2::BigQueryTable]
    #     Required. Auxiliary table location.
    # @!attribute [rw] quasi_ids
    #   @return [::Array<::Google::Cloud::Dlp::V2::PrivacyMetric::KMapEstimationConfig::AuxiliaryTable::QuasiIdField>]
    #     Required. Quasi-identifier columns.
    # @!attribute [rw] relative_frequency
    #   @return [::Google::Cloud::Dlp::V2::FieldId]
    #     Required. The relative frequency column must contain a floating-point
    #     number between 0 and 1 (inclusive). Null values are assumed to be zero.
    class AuxiliaryTable
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # A quasi-identifier column has a custom_tag, used to know which column
      # in the data corresponds to which column in the statistical model.
      # @!attribute [rw] field
      #   @return [::Google::Cloud::Dlp::V2::FieldId]
      #     Identifies the column.
      # @!attribute [rw] custom_tag
      #   @return [::String]
      #     A auxiliary field.
      class QuasiIdField
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end

  # δ-presence metric, used to estimate how likely it is for an attacker to
  # figure out that one given individual appears in a de-identified dataset.
  # Similarly to the k-map metric, we cannot compute δ-presence exactly without
  # knowing the attack dataset, so we use a statistical model instead.
  # @!attribute [rw] quasi_ids
  #   @return [::Array<::Google::Cloud::Dlp::V2::QuasiId>]
  #     Required. Fields considered to be quasi-identifiers. No two fields can
  #     have the same tag.
  # @!attribute [rw] region_code
  #   @return [::String]
  #     ISO 3166-1 alpha-2 region code to use in the statistical modeling.
  #     Set if no column is tagged with a region-specific InfoType (like
  #     US_ZIP_5) or a region code.
  # @!attribute [rw] auxiliary_tables
  #   @return [::Array<::Google::Cloud::Dlp::V2::StatisticalTable>]
  #     Several auxiliary tables can be used in the analysis. Each custom_tag
  #     used to tag a quasi-identifiers field must appear in exactly one
  #     field of one auxiliary table.
  class DeltaPresenceEstimationConfig
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end