Class: Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta2PrivacyMetric

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
generated/google/apis/dlp_v2beta2/classes.rb,
generated/google/apis/dlp_v2beta2/representations.rb,
generated/google/apis/dlp_v2beta2/representations.rb

Overview

Privacy metric to compute for reidentification risk analysis.

Instance Attribute Summary collapse

Instance Method Summary collapse

Methods included from Core::JsonObjectSupport

#to_json

Methods included from Core::Hashable

process_value, #to_h

Constructor Details

#initialize(**args) ⇒ GooglePrivacyDlpV2beta2PrivacyMetric

Returns a new instance of GooglePrivacyDlpV2beta2PrivacyMetric



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# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 4814

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

Instance Attribute Details

#categorical_stats_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta2CategoricalStatsConfig

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

Returns:



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# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 4786

def categorical_stats_config
  @categorical_stats_config
end

#k_anonymity_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta2KAnonymityConfig

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

Returns:



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# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 4791

def k_anonymity_config
  @k_anonymity_config
end

#k_map_estimation_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta2KMapEstimationConfig

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

Returns:



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# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 4801

def k_map_estimation_config
  @k_map_estimation_config
end

#l_diversity_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta2LDiversityConfig

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

Returns:



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# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 4806

def l_diversity_config
  @l_diversity_config
end

#numerical_stats_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta2NumericalStatsConfig

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

Returns:



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# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 4812

def numerical_stats_config
  @numerical_stats_config
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 4819

def update!(**args)
  @categorical_stats_config = args[:categorical_stats_config] if args.key?(:categorical_stats_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