Class: Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta1PrivacyMetric

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) ⇒ GooglePrivacyDlpV2beta1PrivacyMetric

Returns a new instance of GooglePrivacyDlpV2beta1PrivacyMetric



1204
1205
1206
 
# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 1204

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

Instance Attribute Details

#categorical_stats_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta1CategoricalStatsConfig

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

Returns:



1176
1177
1178
 
# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 1176

def categorical_stats_config
  @categorical_stats_config
end

#k_anonymity_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta1KAnonymityConfig

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

Returns:



1181
1182
1183
 
# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 1181

def k_anonymity_config
  @k_anonymity_config
end

#k_map_estimation_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta1KMapEstimationConfig

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:



1191
1192
1193
 
# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 1191

def k_map_estimation_config
  @k_map_estimation_config
end

#l_diversity_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta1LDiversityConfig

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

Returns:



1196
1197
1198
 
# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 1196

def l_diversity_config
  @l_diversity_config
end

#numerical_stats_config ⇒ Google::Apis::DlpV2beta2::GooglePrivacyDlpV2beta1NumericalStatsConfig

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

Returns:



1202
1203
1204
 
# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 1202

def numerical_stats_config
  @numerical_stats_config
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



1209
1210
1211
1212
1213
1214
1215
 
# File 'generated/google/apis/dlp_v2beta2/classes.rb', line 1209

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