Adaptive Spam Detection Inspired by a Cross-Regulation Model of Immune Dynamics: A Study of Concept Drift

Abstract. This paper proposes a novel solution to spam detection inspired by a model of the adaptive immune system known as the crossregulation model. We report on the testing of a preliminary algorithm on six e-mail corpora. We also compare our results statically and dynamically with those obtained by the Naive Bayes classifier and another binary classification method we developed previously for biomedical text-mining applications. We show that the cross-regulation model is competitive against those and thus promising as a bio-inspired algorithm for spam detection in particular, and binary classification in general.

• Type: Journal
• Year: 2008
• Where: CORR
• Authors: Alaa Abi-Haidar, Luis Mateus Rocha
• Keywords: Binary Classification, Binary Classification Method, CORR 2008, Education, Naive Bayes Classifier