de Lemos, Rogério, Timmis, Jon, Ayara, Modupe, Forrest, Simon (2007) Immune-inspired adaptable error detection for automated teller machines. IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews, 37 (5). pp. 873-886. ISSN 1094-6977. (doi:10.1109/TSMCC.2007.900662) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:2028)
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Official URL: http://dx.doi.org/10.1109/TSMCC.2007.900662 |
Abstract
This paper presents an immune-inspired adaptable error detection (AED) framework for automated teller machines (ATMs). This framework has two levels: one is local to a single ATM, while the other is network-wide. The framework employs 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 proposed approach was confirmed in terms of classification performance and impact on availability. The overall results are encouraging as the downtime of ATMs can de reduced by anticipating the occurrence of failures before they actually occur.
Item Type: | Article |
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DOI/Identification number: | 10.1109/TSMCC.2007.900662 |
Uncontrolled keywords: | adaptable error detection (AED); artificial immune systems (AIS); automated teller machines (ATMs); availability; fault tolerance |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Stephen Holland |
Date Deposited: | 19 Dec 2007 19:24 UTC |
Last Modified: | 16 Nov 2021 09:40 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/2028 (The current URI for this page, for reference purposes) |
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