When Machine Unlearning Jeopardizes Privacy

Understand

The right to be forgotten states that a data owner has the right to erase their data from an entity storing it.

• In the context of machine learning (ML), the right to be forgotten requires an ML model owner to remove the data owner's data from the training set used to build the ML model, a process known as machine unlearning.
• While originally designed to protect the privacy of the data owner, we argue that machine unlearning may leave some imprint of the data in the ML model and thus create unintended privacy risks.
• In this paper, we perform the first study on investigating the unintended information leakage caused by machine unlearning.