Genomics Inform.  2016 Mar;14(1):20-28. 10.5808/GI.2016.14.1.20.

The OAuth 2.0 Web Authorization Protocol for the Internet Addiction Bioinformatics (IABio) Database

Affiliations
  • 1Department of Computer Science and Information Engineering, Inha University, Incheon 22212, Korea.
  • 2Department of Medical Informatics College of Medicine, and Institute of Healthcare Management, The Catholic University of Korea, Seoul 06591, Korea. iychoi@catholic.ac.kr
  • 3Department of Information System, Hanyang University, Seoul 04763, Korea.
  • 4Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.

Abstract

Internet addiction (IA) has become a widespread and problematic phenomenon as smart devices pervade society. Moreover, internet gaming disorder leads to increases in social expenditures for both individuals and nations alike. Although the prevention and treatment of IA are getting more important, the diagnosis of IA remains problematic. Understanding the neurobiological mechanism of behavioral addictions is essential for the development of specific and effective treatments. Although there are many databases related to other addictions, a database for IA has not been developed yet. In addition, bioinformatics databases, especially genetic databases, require a high level of security and should be designed based on medical information standards. In this respect, our study proposes the OAuth standard protocol for database access authorization. The proposed IA Bioinformatics (IABio) database system is based on internet user authentication, which is a guideline for medical information standards, and uses OAuth 2.0 for access control technology. This study designed and developed the system requirements and configuration. The OAuth 2.0 protocol is expected to establish the security of personal medical information and be applied to genomic research on IA.

Keyword

access control; IABio; internet addiction; internet user authentication; OAuth 2.0

MeSH Terms

Computational Biology*
Databases, Genetic
Diagnosis
Health Expenditures
Humans
Internet*
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