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Domain 4Objective 4
Model Privacy Attacks COASP Practice Questions (Page 9)
Part of the Adversarial Machine Learning and Model Privacy Attacks domain, which makes up ~13% of our current practice bank.
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Questions 41–42
- 41
A bank uses a credit scoring model that takes an applicant's age, income, and loan amount as inputs. The model's prediction is used to approve or deny loans. A privacy auditor wants to test whether an attacker could infer an applicant's gender (a sensitive attribute not used as an input) from the model's prediction. Which attack should the auditor simulate?
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Which metric measures the proportion of positive predictions that are actually correct in a privacy attack?
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