Class: Google::Apis::DlpV2::GooglePrivacyDlpV2PrivacyMetric

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/dlp_v2/classes.rb,
lib/google/apis/dlp_v2/representations.rb,
lib/google/apis/dlp_v2/representations.rb

Overview

Privacy metric to compute for reidentification risk analysis.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GooglePrivacyDlpV2PrivacyMetric

Returns a new instance of GooglePrivacyDlpV2PrivacyMetric.



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# File 'lib/google/apis/dlp_v2/classes.rb', line 4940

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#categorical_stats_configGoogle::Apis::DlpV2::GooglePrivacyDlpV2CategoricalStatsConfig

Compute numerical stats over an individual column, including number of distinct values and value count distribution. Corresponds to the JSON property categoricalStatsConfig



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# File 'lib/google/apis/dlp_v2/classes.rb', line 4904

def categorical_stats_config
  @categorical_stats_config
end

#delta_presence_estimation_configGoogle::Apis::DlpV2::GooglePrivacyDlpV2DeltaPresenceEstimationConfig

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. Corresponds to the JSON property deltaPresenceEstimationConfig



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# File 'lib/google/apis/dlp_v2/classes.rb', line 4912

def delta_presence_estimation_config
  @delta_presence_estimation_config
end

#k_anonymity_configGoogle::Apis::DlpV2::GooglePrivacyDlpV2KAnonymityConfig

k-anonymity metric, used for analysis of reidentification risk. Corresponds to the JSON property kAnonymityConfig



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# File 'lib/google/apis/dlp_v2/classes.rb', line 4917

def k_anonymity_config
  @k_anonymity_config
end

#k_map_estimation_configGoogle::Apis::DlpV2::GooglePrivacyDlpV2KMapEstimationConfig

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. Corresponds to the JSON property kMapEstimationConfig



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# File 'lib/google/apis/dlp_v2/classes.rb', line 4927

def k_map_estimation_config
  @k_map_estimation_config
end

#l_diversity_configGoogle::Apis::DlpV2::GooglePrivacyDlpV2LDiversityConfig

l-diversity metric, used for analysis of reidentification risk. Corresponds to the JSON property lDiversityConfig



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# File 'lib/google/apis/dlp_v2/classes.rb', line 4932

def l_diversity_config
  @l_diversity_config
end

#numerical_stats_configGoogle::Apis::DlpV2::GooglePrivacyDlpV2NumericalStatsConfig

Compute numerical stats over an individual column, including min, max, and quantiles. Corresponds to the JSON property numericalStatsConfig



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# File 'lib/google/apis/dlp_v2/classes.rb', line 4938

def numerical_stats_config
  @numerical_stats_config
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/dlp_v2/classes.rb', line 4945

def update!(**args)
  @categorical_stats_config = args[:categorical_stats_config] if args.key?(:categorical_stats_config)
  @delta_presence_estimation_config = args[:delta_presence_estimation_config] if args.key?(:delta_presence_estimation_config)
  @k_anonymity_config = args[:k_anonymity_config] if args.key?(:k_anonymity_config)
  @k_map_estimation_config = args[:k_map_estimation_config] if args.key?(:k_map_estimation_config)
  @l_diversity_config = args[:l_diversity_config] if args.key?(:l_diversity_config)
  @numerical_stats_config = args[:numerical_stats_config] if args.key?(:numerical_stats_config)
end