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The scalability and the strategy for EMR database encryption techniques

Shin, David, Sahama, Tony R., Kim, Steve (Jung Tae), & Kim, Ji-hong (2011) The scalability and the strategy for EMR database encryption techniques. International Journal of Information and Communication Sciences, 9(5), pp. 577-582.

Abstract

EMR (Electronic Medical Record) is an emerging technology that is highly-blended between non-IT and IT area. One methodology is to link the non-IT and IT area is to construct databases. Nowadays, it supports before and after-treatment for patients and should satisfy all stakeholders such as practitioners, nurses, researchers, administrators and financial departments and so on. In accordance with the database maintenance, DAS (Data as Service) model is one solution for outsourcing. However, there are some scalability and strategy issues when we need to plan to use DAS model properly. We constructed three kinds of databases such as plan-text, MS built-in encryption which is in-house model and custom AES (Advanced Encryption Standard) - DAS model scaling from 5K to 2560K records. To perform custom AES-DAS better, we also devised Bucket Index using Bloom Filter. The simulation showed the response times arithmetically increased in the beginning but after a certain threshold, exponentially increased in the end. In conclusion, if the database model is close to in-house model, then vendor technology is a good way to perform and get query response times in a consistent manner. If the model is DAS model, it is easy to outsource the database, however, some techniques like Bucket Index enhances its utilization. To get faster query response times, designing database such as consideration of the field type is also important. This study suggests cloud computing would be a next DAS model to satisfy the scalability and the security issues.

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ID Code: 50378
Item Type: Journal Article
Keywords: Data encryption, Electronic health record, DAS, Bucket Index, Bloom filter
ISSN: 1738-0235
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2011 Please consult the authors.
Deposited On: 16 May 2012 14:15
Last Modified: 17 Jun 2013 13:27

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