Immunising automated teller machines

Modupe Ayara*, Jon Timmis, Rogério De Lemos, Simon Forrest

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

9 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationArtificial Immune Systems
Subtitle of host publication4th International Conference, ICARIS 2005, Banff, Alberta, Canada, August 14-17, 2005, Proceedings
PublisherSpringer Nature
Number of pages14
Publication statusPublished - 2005
Event4th International Conference on Artificial Immune Systems, ICARIS 2005 - Banff, Alta., Canada
Duration: 14 Aug 200517 Aug 2005

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Nature
ISSN (Print)0302-9743


Conference4th International Conference on Artificial Immune Systems, ICARIS 2005
CityBanff, Alta.
Period14 Aug 200517 Aug 2005


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