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

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
generated/google/apis/dlp_v2/classes.rb,
generated/google/apis/dlp_v2/representations.rb,
generated/google/apis/dlp_v2/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) ⇒ GooglePrivacyDlpV2PrivacyMetric

Returns a new instance of GooglePrivacyDlpV2PrivacyMetric



3454
3455
3456
 
# File 'generated/google/apis/dlp_v2/classes.rb', line 3454

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

Instance Attribute Details

#categorical_stats_config ⇒ Google::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

Returns:



3426
3427
3428
 
# File 'generated/google/apis/dlp_v2/classes.rb', line 3426

def categorical_stats_config
  @categorical_stats_config
end

#k_anonymity_config ⇒ Google::Apis::DlpV2::GooglePrivacyDlpV2KAnonymityConfig

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

Returns:



3431
3432
3433
 
# File 'generated/google/apis/dlp_v2/classes.rb', line 3431

def k_anonymity_config
  @k_anonymity_config
end

#k_map_estimation_config ⇒ Google::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

Returns:



3441
3442
3443
 
# File 'generated/google/apis/dlp_v2/classes.rb', line 3441

def k_map_estimation_config
  @k_map_estimation_config
end

#l_diversity_config ⇒ Google::Apis::DlpV2::GooglePrivacyDlpV2LDiversityConfig

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

Returns:



3446
3447
3448
 
# File 'generated/google/apis/dlp_v2/classes.rb', line 3446

def l_diversity_config
  @l_diversity_config
end

#numerical_stats_config ⇒ Google::Apis::DlpV2::GooglePrivacyDlpV2NumericalStatsConfig

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

Returns:



3452
3453
3454
 
# File 'generated/google/apis/dlp_v2/classes.rb', line 3452

def numerical_stats_config
  @numerical_stats_config
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



3459
3460
3461
3462
3463
3464
3465
 
# File 'generated/google/apis/dlp_v2/classes.rb', line 3459

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