Artificial immune for harmful information filtering

Abstract

Biologically-inspired methods such as evolutionary algorithms and neural networks are well suited to dynamic problems. Artificial immune systems are proving useful in the field of information filtering. We tackle this dynamic problem with IHIF, a harmful information filtering model inspired by the immune system. It is based on a self-organising antibody network that reacts to dynamic evolvement in order to define and preserve the features of harmful Web pages. The experiment results demonstrate IHIF's ability to filter harmful information. © 2011 Springer-Verlag Berlin Heidelberg.