Biblio

E-mail is widespread and an essential communication technology in modern times. Since e-mail has problems with spam mails and spoofed e-mails, countermeasures are required. Although SPF, DKIM and DMARC have been proposed as sender domain authentication, these mechanisms cannot detect non-spoofing spam mails. To overcome this issue, this paper proposes a method to detect spam domains by supervised learning with features extracted from e-mail reception log and active DNS data, such as the result of Sender Authentication, the Sender IP address, the number of each DNS record, and so on. As a result of the experiment, our method can detect spam domains with 88.09% accuracy and 97.11% precision. We confirmed that our method can detect spam domains with detection accuracy 19.40% higher than the previous study by utilizing not only active DNS data but also e-mail reception log in combination.