# README

This file contains the source codes for USENIX Security'25 submission "SoK: On Gradient Leakage in Federated Learning"

## Requirements for the Environment
Please refer to "requirements.txt".

## Datasets
All the datasets utilized in this paper are public available. You could qulickly download them from the following URLs:

1. CIFAR10: https://www.cs.toronto.edu/~kriz/cifar.html
2. CIFAR100: https://www.cs.toronto.edu/~kriz/cifar.html
3. ImageNet-1K: https://www.image-net.org/download.php
4. ImageNet-21K: https://huggingface.co/datasets/zeyuanyin/imagenet-21k-p
5. CelebA: https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
6. Places: https://github.com/deeplearning-wisc/large_scale_ood
7. Textures: https://www.robots.ox.ac.uk/~vgg/data/dtd/
8. Styles: https://datasets.activeloop.ai/docs/ml/datasets/pacs-dataset/

## Scripts and Source Codes
We have organized the codes in section and chart order, please refer to the relevant files ("Section4.zip", "Section5.zip", "Section6.zip").
The codes for experiments in the appendix are also included.

## Acknowledgment
Our codes reference previous works on gradient inversion attacks:
1. https://github.com/JonasGeiping/invertinggradients
2. https://github.com/ml-postech/gradient-inversion-generative-image-prior