Adaptive Spam Detection Inspired by the Immune System

This paper proposes a novel solution to spam detection inspired by a model of the adaptive immune system known as the cross-regulation model. We report on the testing of a preliminary algorithm on six e-mail corpora. We also compare our results with those obtained by the Naive Bayes classifier and another binary classification method we developed previously for biomedical text-mining applications. We obtained very encouraging results which can be further improved with development of this bio-inspired model. We show that the cross-regulation model is promising as a bio-inspired algorithm for spam detection in particular, and binary classification in general. Finally, we also present evidence that our bio-inspired model is relevant for understanding immune regulation itself.

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