Cloud Computing

SP5 — Processing sensitive medical information in cloud computing environments while ensuring information security & privacy

In recent years cloud computing has gained tremendous recognition by researchers and practitioners for offering seemingly unlimited resources in a timely and on-demand manner. Nowadays cloud computing and modern sequencing techniques enable medical professionals as well as researchers to perform DNA sequencing at ever-decreasing durations and costs. As a result, affordable DNA sequencing helps researchers and medical professionals to better understand the processes inside the human body, leading to improved treatment of diseases.

Despite these benefits, cloud computing also bears risks in terms of information security and privacy for data stored in the cloud. This is especially relevant in case of medical data, which is highly sensitive and, therefore, deserves special protection. Even more so genetic information (i.e., DNA samples) represents one of the most private and sensitive types of data, containing such information as one's family relationships or diseases. While people and especially patients will benefit from the majority of applications of DNA analyses, we are also aware of the social and privacy-related risks that accompany such technology, especially, when used in an undesired or unlawful way.

To address the above risks our sub-project's overall research objective is to ensure adequate information security and privacy of medical, and, especially genomic, data in cloud computing environments. Within the MILES project our aims are to:

  • Aim 1. Establish a taxonomy of data relevant for MILES
  • Aim 2. Identify cloud deployment models and fitting security measures ensuring integrity and confidentiality of data
  • Aim 3. Develop a framework for selecting deployment models and security measures in medical cloud contexts
Based upon the results of our research, cloud computing providers will be able to design safe and secure cloud computing environments for medical data.