Class: Google::Apis::DlpV2::GooglePrivacyDlpV2PrivacyMetric
- Inherits:
-
Object
- Object
- Google::Apis::DlpV2::GooglePrivacyDlpV2PrivacyMetric
- 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
-
#categorical_stats_config ⇒ Google::Apis::DlpV2::GooglePrivacyDlpV2CategoricalStatsConfig
Compute numerical stats over an individual column, including number of distinct values and value count distribution.
-
#delta_presence_estimation_config ⇒ Google::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.
-
#k_anonymity_config ⇒ Google::Apis::DlpV2::GooglePrivacyDlpV2KAnonymityConfig
k-anonymity metric, used for analysis of reidentification risk.
-
#k_map_estimation_config ⇒ Google::Apis::DlpV2::GooglePrivacyDlpV2KMapEstimationConfig
Reidentifiability metric.
-
#l_diversity_config ⇒ Google::Apis::DlpV2::GooglePrivacyDlpV2LDiversityConfig
l-diversity metric, used for analysis of reidentification risk.
-
#numerical_stats_config ⇒ Google::Apis::DlpV2::GooglePrivacyDlpV2NumericalStatsConfig
Compute numerical stats over an individual column, including min, max, and quantiles.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GooglePrivacyDlpV2PrivacyMetric
constructor
A new instance of GooglePrivacyDlpV2PrivacyMetric.
-
#update!(**args) ⇒ Object
Update properties of this object.
Methods included from Core::JsonObjectSupport
Methods included from Core::Hashable
Constructor Details
#initialize(**args) ⇒ GooglePrivacyDlpV2PrivacyMetric
Returns a new instance of GooglePrivacyDlpV2PrivacyMetric.
4402 4403 4404 |
# File 'generated/google/apis/dlp_v2/classes.rb', line 4402 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
4366 4367 4368 |
# File 'generated/google/apis/dlp_v2/classes.rb', line 4366 def categorical_stats_config @categorical_stats_config end |
#delta_presence_estimation_config ⇒ Google::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
4374 4375 4376 |
# File 'generated/google/apis/dlp_v2/classes.rb', line 4374 def delta_presence_estimation_config @delta_presence_estimation_config end |
#k_anonymity_config ⇒ Google::Apis::DlpV2::GooglePrivacyDlpV2KAnonymityConfig
k-anonymity metric, used for analysis of reidentification risk.
Corresponds to the JSON property kAnonymityConfig
4379 4380 4381 |
# File 'generated/google/apis/dlp_v2/classes.rb', line 4379 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
4389 4390 4391 |
# File 'generated/google/apis/dlp_v2/classes.rb', line 4389 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
4394 4395 4396 |
# File 'generated/google/apis/dlp_v2/classes.rb', line 4394 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
4400 4401 4402 |
# File 'generated/google/apis/dlp_v2/classes.rb', line 4400 def numerical_stats_config @numerical_stats_config end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
4407 4408 4409 4410 4411 4412 4413 4414 |
# File 'generated/google/apis/dlp_v2/classes.rb', line 4407 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 |