Abstract

This paper introduces the Voronoi diagram-based Artificial Immune System (VorAIS). VorAIS models the self/non-self using a Voronoi diagram that determines which areas of the problem domain correspond to self or to non-self. The diagram is evolved using a multi-objective bio-inspired approach in order to conjointly optimize various classification metrics (accuracy, recall and specificity). VorAIS is experimentally validated, first on standard classification problems, then on the well-known NSL-KDD dataset for anomaly detection where it favorably compares with other AIS approaches.