← All writing

Label-Only Membership Inference

2 parts, in reading order.

  1. Part 1
    What is a membership inference attack?

    The first in a series cataloguing my journey reproducing papers I want to properly understand. Starting with the core idea and vocabulary of membership inference attacks.

  2. Part 2
    The gap attack, and some ML fundamentals

    To build the gap attack I first had to learn how to train a neural network, so this post is mostly the ML setup (CNNs, tensors, loss, gradient descent), with the working attack at the end.