Abstract Passwords remain the most widely used authentication method and play a critical role in maintaining practical security. Previous research has highlighted the influence of linguistic factors on the strength of user-created passwords, demonstrating that evaluating passwords created by users speaking languages other than English requires specific contextual knowledge. Despite this, no prior studies have specifically investigated the passwords of Japanese users. This paper presents the first study of the characteristics of Japanese user-created passwords across websites offering five types of services. Using a dataset of 48.5 million real-world leaked passwords, we conduct a comprehensive analysis of various aspects of password behavior. Our findings reveal several unique characteristics of Japanese web passwords. For instance, Japanese passwords exhibit greater dispersion compared to those of English and Chinese users, with keyboard-walk patterns being particularly prevalent among the most frequently used passwords. To address these findings, we propose a suggestion for helping users improve their password selection strategies. The experimental results demonstrate that the suggestion led to 82.15% and 93.88% of passwords being strengthened as evaluated by two effective PSMs, and reduced the cracking success rate of PCFG-guesser by up to 56.12%.

Abstract Visual cryptography (VC) is a powerful technique with high security and requires no PC or device to reconstruct the secret information. Progressive visual cryptography (PVC) is a variation of the VC scheme in which the quality of the reconstructed image is improved by increasing the number of shared images. The previous study focused directly on maximizing the value of the quality in the completely reconstructed image; thus, there is a difference in the quality of the shared images. In this paper, we focus on the aforementioned issue and propose a new approach based on inductive reasoning. Our basic idea is to maximize the quality of the reconstructed images each time the number of shared images increases. We call this method the bottom-up approach. Moreover, hitherto, PVC has been evaluated based on the value of relative difference or by sight. Such evaluation methods are only subjective or difficult to execute without the knowledge of basis matrices. In addition, PVC users cannot easily confirm the effectiveness of their shared images. In this paper, we propose a new information-theoretic evaluation method for PVC, which only uses shared images, to solve the aforementioned problems. Our proposed method can objectively and quantitatively evaluate PVC based on the numerical value, and PVC users can easily confirm the effectiveness of their shared images.