Internationalized domain names (IDNs) are abused to create domain names that are visually similar to those of legitimate/popular brands. In this work, we systematize such domain names, which we call deceptive IDNs, and analyze the risks associated with them. In particular, we propose a new system called DomainScouter to detect various deceptive IDNs and calculate a deceptive IDN score, a new metric indicating the number of users that are likely to be misled by a deceptive IDN. We perform a comprehensive measurement study on the identified deceptive IDNs using over 4.4 million registered IDNs under 570 top-level domains (TLDs). The measurement results demonstrate that there are many previously unexplored deceptive IDNs targeting non-English brands or combining other domain squatting methods. Furthermore, we conduct online surveys to examine and highlight vulnerabilities in user perceptions when encountering such IDNs. Finally, we discuss the practical countermeasures that stakeholders can take against deceptive IDNs.

This work aims to determine the propensity of password creation through the lens of language spheres. To this end, we consider four different countries, each with a different culture/language: China/Chinese, United Kingdom (UK) and India/English, and Japan/Japanese. We first employ a user study to verify whether language and culture are reflected in password creation. We found that users in India, Japan, and the UK prefer to create their passwords from base words, and the kinds of words they are incorporated into passwords vary between countries. We then test whether the findings obtained through the user study are reflected in a corpus of leaked passwords. We found that users in China and Japan prefer dates, while users in India, Japan, and the UK prefer names. We also found that cultural words (e.g., “sakura” in Japan and “football” in the UK) are frequently used to create passwords. Finally, we demonstrate that the knowledge on the linguistic background of targeted users can be exploited to increase the speed of the password guessing process.