Immunising Automated Teller Machines

Abstract. This paper presents an immune-inspired adaptable error detection (AED) framework for Automated Teller Machines (ATMs). This framework two levels, one level is local to a single ATM, while the other is a network-wide adaptable error detection. It employs ideas from vaccination, and adaptability analogies of the immune system. For discriminating between normal and erroneous states, an immune inspired one-class supervised algorithm was employed, which supports continual learning and adaptation. The effectiveness of the local AED was confirmed by its ability of detecting potential failures on an average 3 hours before the actual occurrence. This is an encouraging result in terms of availability, since measures can be devised for reducing the downtime of ATMs.

• Type: Conference
• Year: 2005
• Where: ICARIS
• Authors: Modupe Ayara, Jon Timmis, Rogério de Lemos, Simon Forrest
• Keywords: Adaptable Error Detection, ICARIS 2005, Immune-inspired Adaptable Error, Network-wide Adaptable Error