Improved Wordpcfg for Passwords with Maximum Probability Segmentation

Improved Wordpcfg for Passwords with Maximum Probability Segmentation

Li, Wenting (Peking University)
Yang, Jiahong (Peking University)
Cheng, Haibo (Peking University)
Wang, Ping (Peking University)
Liang, K. (TU Delft Cyber Security)

2023

Modeling password distributions is a fundamental problem in password security, benefiting the research and applications on password guessing, password strength meters, honey password vaults, etc. As one of the best segment-based password models, WordPCFG has been proposed to capture individual semantic segments (called words) in passwords. However, we find WordPCFG does not address well the ambiguity of password segmentation by maximum matching, leading to the unreasonable segmentation of many password and further the inaccuracy of modeling password distributions. To address the ambiguity, we improve WordPCFG by maximum probability segmentation with A*-like pruning algorithm. The experimental results show that the improved WordPCFG cracks 99.26%–99.95% passwords, with nearly 5.67%–18.01% improvement.

Password
Probabilistic context-free grammar
maximum probability segmentation

http://resolver.tudelft.nl/uuid:03dd1891-0d72-4e6b-9d6b-6f0dc87491ca

https://doi.org/10.1109/ICASSP49357.2023.10096535

IEEE, Piscataway

2023-11-05

978-1-7281-6328-4

Proceedings of the ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

48th IEEE International Conference on Acoustics, Speech and Signal Processing 2023, 2023-06-04 → 2023-06-10, Rhodes Island, Greece

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2023 Wenting Li, Jiahong Yang, Haibo Cheng, Ping Wang, K. Liang