Chung-Kwei: a Pattern-discovery-based System for the Automatic Identification of Unsolicited E-mail Messages (SPAM).
Isidore Rigoutsos, Tien Huynh · 2004
In this paper, we present Chung-Kwei , a system for the analysis of electronic messages and the automatic identification of unsolicited email messages (=SPAM). The method uses pattern-discovery as its underlying tool and is another instance of a generic approach that has been the basis of previously successful solutions developed by our group to tackle problems in computational biology such as gene finding and protein annotation. ChungKwei can be trained very quickly; as new examples of SPAM become available, the system can re-train itself without interrupting the classification of incoming e-mail. We trained Chung-Kwei on a repository of 87,000 messages, then tested it with a very large collection of 88,000 pieces of SPAM and WHITE email: the current prototype achieved a sensitivity of 96.56% whereas the false positive rate was 0.066%, or one-in-six-thousand. In terms of speed, we are currently capable of classifying 214 messages/second, on a 2.2 GHz Intel-Pentium platform. The Chung-Kwei system is part of SpamGuru, a collaborative antispam filtering solution that is currently under development at IBM Research.