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Threats identification in healthcare information systems using genetic algorithm and cox regression

Ahmad, R., Samy, G.N., Ibrahim, N.K., Bath, P.A. and Ismail, Z. (2010) Threats identification in healthcare information systems using genetic algorithm and cox regression. Journal of Information Assurance and Security , 5 (1). pp. 154-161. ISSN 1554-1010

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Threats to information security for healthcare information system increased tremendously. There are various factors contribute to information security threats, many researchers focused only to certain factors which interest them (e.g., virus attack). Certain factors which may be important remain unexplored. In addition, lack of tools and technologies directed to limited number of threats traced in healthcare system. Thus it introduces bias in threat analysis. This study explored the use of biological computational termed Genetic Algorithm (GAs) combined with Cox regression (CoRGA) in identifying a potential threat for healthcare system. The results show that variable described “misused of e-mail” is the major information security threats for healthcare system. Results were compared with manual analysis using the same data, and it is shows that GAs not just introducing new threats for healthcare system but it was similar with others threats proposed by previous researches.

Item Type: Article
Keywords: Healthcare Information Systems (HIS), Risk Analysis, Threats, Information Security, Genetic Algorithm and Cox Regression
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
Depositing User: Miss Anthea Tucker
Date Deposited: 26 Feb 2010 11:48
Last Modified: 26 Feb 2010 11:48
Published Version: http://www.mirlabs.org/jias/index.html
Status: Published
Publisher: Dynamic Publishers Inc.
URI: http://eprints.whiterose.ac.uk/id/eprint/10441

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