Spam Miner: A Platform for Detecting and Characterizing Spam Campaigns
Pedro Guerra, Douglas E. V. Pires, Marco Túlio, Carlos Ribeiro, Dorgival O. Guedes, Wagner Meira, Cristine Hoepers, Marcelo H. P. C. Chaves, Klaus Steding-Jessen · 2009
This demo presents Spam Miner, an online system designed for real-time monitoring and characterization of spam traf-fic over the Internet. Our system is based on high-level abstractions such as spam message attributes, spam cam-paigns and spamming strategies. A campaign is a cluster of messages that are generated from a single message tem-plate; campaign identification is a challenging problem be-cause it has to handle spammer evolution, while seeking for a spam similarity function that combines different message characteristics and for strategies that efficiently process large volumes of spams. Moreover, spam campaigns need to be identified on-the-fly, to allow incident response teams and security specialists to react to the threat adequately. Spam Miner addresses campaign identification as a data clustering