Attribute inference attack risk for AI
An attribute inference attack is used to detect whether certain sensitive features can be inferred about individuals who participated in training a model. These attacks occur when an adversary has some prior knowledge about the training data and uses that knowledge to infer the sensitive data.
Why is attribute inference attack a concern for foundation models?
With a successful attack, the attacker can gain valuable information such as sensitive personal information or intellectual property.
Parent topic: AI risk atlas