A Study on the Measuring Methods of Website Security Risk Rate

Abstract

Traditionally, website security risks are measured using static analysis based on patterns and dynamic analysis by accessing websites with user devices. Recently, similarity hash-based website security risk analysis and machine learning-based website security risk analysis methods have been proposed. In this study, we propose a technique to measure website risk by collecting public information on the Internet. Publicly available DNS information, IP information, and website reputation information were used to measure security risk. Website reputation information includes global traffic rankings, malware distribution history, and HTTP access status. In this study, we collected public information on a total of 2000 websites, including 1000 legitimate domains and 1000 malicious domains, to assess their security risk. We evaluated 11 categories of public information collected by the Korea Internet & Security Agency, an international domain registrar. Through this study, public information about websites can be collected and used to measure website security risk.