8 accepted papers
Password guessing attack is a significant threat to account security. Understanding this attack is crucial for identifying the vulnerabilities of current password systems and for developing more effective methods to protect user accounts. Adaptive password guessing techniques can dynamically adjust…
With the increasing prevalence of personal information breaches, targeted password guessing based on user-specific data has emerged as a serious security threat. Existing targeted password guessing attacks primarily rely on traditional statistical language models, which have limited capability in ad…
Variational Autoencoder (VAE) has been used as password generative model for trawling attack in multiple works. Its sample distribution can be easily changed by controling the mean and variance of the prior distribution, which makes it natively suitable for dynamic attack scenario. Combining transfo…
Passwords are widely used for website authentication, but they are vulnerable to guessing attacks. To measure password guessability, the commonly used approach involves modeling the distribution of passwords with a password probability model and then estimating the guessability using Monte Carlo met…
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 seman…
Passwords have been widely used in online authentication, and they form the front line that protects our data security and privacy. But the security of password may be easily harmed by insecure password generator. Massive reports state that users are always keen to generate new passwords by reusing…
To date there are few researches on the semantic information of passwords, which leaves a gap preventing us from fully understanding the passwords characteristic and security. We propose a new password probability model for semantic information based on Markov Chain with both generalization and accu…
Probabilistic context-free grammars (PCFGs) have been pro-posed to capture password distributions, and further been used in password guessing attacks and password strength meters. However, current PCFGs suffer from the limitation of inaccurate segmentation of password, which leads to misestimation o…