Revealing social networks of spammers through spectral clustering

Xu, Kevin S., Kliger, Mark, Chen, Yilun, Woolf, Peter J., Hero, Alfred O. III

arXiv.org Machine Learning 

Previous studies on spam have mostly focused on studying its content or its source. Likewise, currently used anti-spam methods mostly involve filtering emails based on their content or by their email server IP address. More recently, there have been studies on the network-level behavior of spammers [1], [2]. However, very little attention has been devoted to studying how spammers acquire the email addresses that they send spam to, a process commonly referred to as harvesting. Harvesting is the first phase of the spam cycle; sending the spam emails to the acquired addresses is the second phase. Spammers send spam emails using spam servers, which are typically compromised computers or open proxies, both of which allow spammers to hide their identities. On the other hand, it has been observed that spammers do not make the same effort to conceal their identities during the harvesting phase [3], indicating that harvesters, which are individuals or bots that collect email addresses, are closely related to the spammers who are sending the spam emails. The harvester and spam server are the two intermediaries in the path of spam, illustrated in Figure 1. In this paper we try to reveal social networks of spammers by identifying communities of harvesters using data from both phases of the spam cycle.

Duplicate Docs Excel Report

Title
None found

Similar Docs  Excel Report  more

TitleSimilaritySource
None found