This repository is created for the review process of paper "HoneyGAN: Creating Indistinguishable Honeywords with Improved Generative Adversarial Networks."
HoneyGAN is a honeyword generation technique (HGT) based on GNPassGAN.
The datasets in the real passwords folder are taken from BitBucket.
python3 -m venv .venv
source .venv/bin/activate
pip3 install -r requirements.txt
python3 fasttext.py
Generate honeywords using either HGTs in the paper (0 is GNPassGAN, 1 is tweaking, 2 is fasttext) and get attack success rate.
# change target and attack file path
python3 hgt.py --generated GNpassGAN_generated.txt \
--path-target real_passwords/rockyou_sorted_preprocessed.txt \
--path-attack real_passwords/dubsmash-com_sorted_preprocessed.txt \
--hgt 0
# change the path of the tested file
python3 inner_similarity.py --path-sweetwords sweetwords/chaffing_by_tweak/rockyou_10000_20.txt