A threat actor gains access to a publicly available AI model's API and uses it to determine whether specific individuals' records were used in training. Which attack does this describe?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because membership inference attacks query a model's API to determine whether a specific data point was part of the training dataset, posing significant privacy risks. A is wrong because model extraction replicates model functionality, not determines training membership.
Full explanation below image
Full Explanation
B is correct because membership inference attacks query a model's API to determine whether a specific data point was part of the training dataset, posing significant privacy risks. A is wrong because model extraction replicates model functionality, not determines training membership. C is not a standard attack category for this scenario. D (gradient inversion) reconstructs training data from gradients, typically in federated learning settings.