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

• Main Authors: Ahmad, Rabiah, Samy, Ganthan Narayana, Ibrahim, Nuzulha Khilwani, Bath, Peter A., Ismail, Zuraini
• Format: Article
• Language: English
• Published: Dynamic Publishers 2010
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/39155/1/vol5-issue2.html; http://eprints.utm.my/id/eprint/39155/
• Institution: Universiti Teknologi Malaysia

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.