One Size Does Not Fit All: Information Security and Information Privacy for Genomic Cloud Services

Abstract

Most extant genomic cloud services strive to maximize information security and information privacy protection thereby neglecting the diversity of information practices in genomic research. Such a one-size-fits-all approach is not expedient and decreases the overall system usability and performance. While there is growing awareness that employed information security and information privacy measures must adapt to information security and information privacy requirements inherent to information practices, limited design knowledge exists on how to actually design genomic cloud services capable to account for differences in information practices in genomic research. In this research-in-progress, we propose a model for genomic cloud services that dynamically adapt to the diverse information security and information privacy requirements in genomic research. Our research contributes to the scientific knowledge base by capturing design knowledge for secure, privacy-preserving, and usable genomic cloud services, accounting for conflicts between information security and information privacy, and fostering understanding of information privacy as a context-sensitive construct.

Keywords: Information Security and Information Privacy, Genomic Cloud Computing, Healthcare Infor-mation Systems, Design Science Research

JEL Classification: L86