Repo for USENIX security 2024 paper "On Data Fabrication in Collaborative Vehicular Perception: Attacks and Countermeasures" Arxiv DOI:10.48550/arXiv.2309.12955
- Python package manager: conda
- GPU (tested on RTX 2080 Ti)
- Free space > 40 GB
# Get the codebase.
git clone --recursive https://github.com/zqzqz/AdvCollaborativePerception.git
cd AdvCollaborativePerception
# Set up the Python environment.
bash scripts/setup.sh
conda activate advCP
# Download data from Google Drive
bash scripts/download.sh
# Run evaluation.
python scripts/evaluate.py
cat result/evaluate.log
The scripts will install dependencies, download dataset from Google Drives, set up the environment, and execute all evaluation tasks. Results are saved to result
by default.
data/OPV2V
: The perception dataset OPV2V and pre-computed meta files.data/carla
: Pre-computed carla maps where OPV2V is collected.data/model_3d
: 3D models that are useful for ray casting attacks.models
: Pretrained models.mvp
: The main module implementing our proposed attack and defense.test
: Examples of usingmvp
to operate datasets, attack methods, etc.
Q: Problems of CUDA and PyTorch.
A: Our script scripts/setup.sh
by default installs PyTorch 1.9.1 and CUDA 10.2. Please adjust the versions if it does not work for your environment. If the conda environment is not working for you, please try downloading the packages from pip, following instructions from PyTorch website.
Q: Deprecated functions of numpy
or shapely
.
A: Our code is tested on numpy==1.19
and shapely==1.8.1
. numpy>=1.20
and shapely>=2.0
may throw warnings or errors about deprecated functions.
Q: Data downloading via scripts/download.sh
is failed.
A: Please try to download data manually from Google Drive websites. The links are detailed in scripts/download.sh
.
Q: Fail to compile CUDA programs.
A: Please make sure the machine has C++ compiling tools installed. For instance, sudo apt-get install build-essential
for Ubuntu OS.