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.


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.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

52 since deposited on 16 May 2012
4 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 50378
Item Type: Journal Article
Refereed: Yes
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 04:15
Last Modified: 17 Jun 2013 03:27

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page