Abstract
TarGuess-I is a leading targeted password guessing model using users’ personally identifiable information (PII) proposed at ACM CCS 2016 by Wang et al. Owing to its superior guessing performance, TarGuess-I has attracted widespread attention in password security. Yet, TarGuess-I fails to capture popular passwords and special strings in passwords correctly. Thus we propose TarGuess-I\( ^+ \): an improved password guessing model, which is capable of identifying popular passwords by generating top-300 most popular passwords from similar websites and grasping special strings by extracting continuous characters from user-generated PII. We conduct a series of experiments on 6 real-world leaked datasets and the results show that our improved model outperforms TarGuess-I by 9.07% on average with 1000 guesses, which proves the effectiveness of our improvements.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.