Trojan Detection Challenge Starter Kit
Update: The validation phase annotations are available here.
This repository contains code for loading data and generating submissions for the Trojan Detection Challenge (TDC) NeurIPS 2022 competition. To learn more, please see the competition website.
Contents
There are four folders corresponding to different tracks and subtracks: 1) Trojan Detection, 2) Trojan Analysis (Target Label Prediction), 3) Trojan Analysis (Trigger Synthesis), and 4) Evasive Trojans. We provide starter code for submitting baselines in example_submission.ipynb under each folder. The tdc_datasets folder is expected to be under the same parent directory as tdc-starter-kit. The datasets are available here. You can download them from the Zenodo website or by running download_datasets.py.
The utils.py file contains helper functions for loading new models, generating new attack specifications, and training clean/Trojaned networks. This is primarily used for the Evasive Trojans Track starter kit. It also contains the load_data function for loading data sources (CIFAR-10/100, GTSRB, MNIST), which may be of general use. To load GTSRB images, unzip gtsrb_preprocessed.zip in the data folder (NOTE: This folder is only for storing data sources. The network datasets are stored in tdc_datasets, which must be downloaded from Zenodo). You may need to adjust the paths in the load_data function depending on your working directory. The wrn.py file contains the definition of the Wide Residual Network class used for CIFAR-10 and CIFAR-100 models. When loading networks from the competition datasets, wrn.py must be in your path. See the example submission notebooks for details.
How to Use
Clone this repository, then download the competition datasets and unzip adjacent to the repository. Ensure that your Jupyter version is up-to-date (fairly recent). To avoid errors with model incompatibility, please use PyTorch version 1.11.0. You can now run one of the example notebooks or start building your own submission.