Awesome
Invisible Backdoor Attack with Sample-Specific Triggers
Environment
This project is developed with Python 3.6 on Ubuntu 18.04. Please run the following script to install the required packages
pip install -r requirements.txt
Demo
Before running the code, please download the checkpoints from Baidudisk (code:o89z), and put them into ckpt
folder.
-
Generating poisoned sample with sample-specific trigger.
# TensorFlow python encode_image.py \ --model_path=ckpt/encoder_imagenet \ --image_path=data/imagenet/org/n01770393_12386.JPEG \ --out_dir=data/imagenet/bd/
Benign image Backdoor image Trigger -
Runing
test.py
for testing benign and poisoned images.# PyTorch python test.py
Train
-
Download data from Baidudisk(code:oxgb) and unzip it to folder
datasets/
. -
Run training script
bash train.sh
. -
The files in checkpoint folder are as following:
--- args.json # Input arguments |-- x_checkpoint.pth.tar # checkpoint |-- x_model_best.pth.tar # best checkpoint |-- x.txt # log file
Defense
Check BackdoorBench for details
Citation
Please cite our paper in your publications if it helps your research:
@inproceedings{li_ISSBA_2021,
title={Invisible Backdoor Attack with Sample-Specific Triggers},
author={Li, Yuezun and Li, Yiming and Wu, Baoyuan and Li, Longkang and He, Ran and Lyu, Siwei},
booktitle={IEEE International Conference on Computer Vision (ICCV)},
year={2021}
}
Notice
This repository is NOT for commecial use. It is provided "as it is" and we are not responsible for any subsequence of using this code.