Adaptive Spam Filtering Based on Fingerprint Vectors

Spam has become one of the severest problems for today´s network systems. In this paper, we present an adaptive spam filtering mechanism based on message fingerprinting. In our mechanism, each message is represented by a fingerprint vector, and two messages with a short distance in their fingerprint vectors are viewed as variants of each other. We present methods for fast matching a query message against a list of known spam messages, and methods for adaptive updating of the fingerprint vectors of known spam messages. Experiments on real spam data demonstrate the effectiveness of the proposed method.