MailRank: using ranking for spam detection

Can we use social networks to combat spam? This paper investigates the feasibility of MailRank, a new email ranking and classification scheme exploiting the social communication network created via email interactions. The underlying email network data is collected from the email contacts of all MailRank users and updated automatically based on their email activities to achieve an easy maintenance. MailRank is used to rate the sender address of arriving emails such that emails from trustworthy senders can be ranked and classified as spam or non-spam. The paper presents two variants: Basic MailRank computes a global reputation score for each email address, whereas in Personalized MailRank the score of each email address is different for each MailRank user. The evaluation shows that MailRank is highly resistant against spammer attacks, which obviously have to be considered right from the beginning in such an application scenario. MailRank also performs well even for rather sparse networks, i.e., where only a small set of peers actually take part in the ranking of email addresses.