@inproceedings{36f2ea68f505405f8078696a496665d7,
title = "PassGAN-based honeywords system",
abstract = "In this work, we simulate a game between the attacker and the defender to evaluate their possible strategies in a honeyword system. For the attacker's guessing strategy, the Top-PW attack is used and a novel PassGAN-based attack is proposed. Meanwhile, for the defender's honeywords generation strategy, a PassGAN-based method is implemented and a novel two-stages PassGAN-based generation strategy is proposed. The experiment results show that the Top-PW attack is generally more successful than the PassGAN-based attack for the attacker while the proposed two-stages PassGAN-based approach is proven to be the most suitable honeyword generation strategy for the defender. The proposed two-stages PassGAN-based method for the defender's generation strategy can decrease the attacker's success rate to 9\% and surpass some previous honeywords generation methods.",
keywords = "Attacker, Deep learning, Defender, Honeywords, PassGAN, Strategy",
author = "Fauzi, \{Muhammad Ali\} and Bian Yang and Edlira Martiri",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019 ; Conference date: 05-12-2019 Through 07-12-2019",
year = "2019",
month = dec,
doi = "10.1109/CSCI49370.2019.00037",
language = "English",
series = "Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "179--184",
booktitle = "Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019",
}