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 paper proposes a new method of realizing internationlized domain names (iDN) and has been discussed at IETF (Internet Engineering Task Force). iDN allows a user to specify multi-lingual domain names, such as Japanese, Chinese, and Korean. iDN is a proper extension of the current domain name system. We have already developed an iDN implementation, named Global Domain Name System (GDNS). GDNS extends the usage of alias records, and gives reverse mapping information for multi-lingual domain names. This paper presents yet another method which introduces new Resource Record (RR) types to cover multi-lingual domain names. We have two new RR (Resource Record) types. The first new record is INAME and the other is IPTR. These two RR types can cover multi-lingual domain names. This paper also discusses the efficiency of DNS. Since DNS is a distributed database system, the performance depends on the method of retrieving data. This paper suggests a new retrieving method that can improve the performance of DNS remarkably.