The medical science DMZ: a network design pattern for data-intensive medical science

Journal Article · Fri Oct 06 00:00:00 EDT 2017 · Journal of the American Medical Informatics Association

DOI:https://doi.org/10.1093/jamia/ocx104· OSTI ID:1779352

Peisert, Sean ^[1]; Dart, Eli ^[2]; Barnett, William ^[3]; Balas, Edward ^[4]; Cuff, James ^[5]; Grossman, Robert L. ^[6]; Berman, Ari ^[7]; Shankar, Anurag ^[8]; Tierney, Brian ^[2]

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1. Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA, Department of Computer Science, University of California Davis, Davis, CA, USA, Corporation for Education Network Initiatives in California (CENIC), Berkeley, CA, USA
2. ESnet, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
3. Indiana Clinical and Translational Sciences Institute and Regenstrief Institute, Indiana University, Indianapolis, IN, USA
4. Global Research Network Operations Center, Indiana University, Bloomington, IN, USA
5. Research Computing, Harvard University, Cambridge, MA, USA
6. Center for Data Intensive Science, University of Chicago, Chicago, USA
7. BioTeam, Middleton, MA, USA
8. Pervasive Technology Institute, Indiana University, Bloomington, IN, USA

Abstract Objective We describe a detailed solution for maintaining high-capacity, data-intensive network flows (eg, 10, 40, 100 Gbps+) in a scientific, medical context while still adhering to security and privacy laws and regulations. Materials and Methods High-end networking, packet-filter firewalls, network intrusion-detection systems. Results We describe a “Medical Science DMZ” concept as an option for secure, high-volume transport of large, sensitive datasets between research institutions over national research networks, and give 3 detailed descriptions of implemented Medical Science DMZs. Discussion The exponentially increasing amounts of “omics” data, high-quality imaging, and other rapidly growing clinical datasets have resulted in the rise of biomedical research “Big Data.” The storage, analysis, and network resources required to process these data and integrate them into patient diagnoses and treatments have grown to scales that strain the capabilities of academic health centers. Some data are not generated locally and cannot be sustained locally, and shared data repositories such as those provided by the National Library of Medicine, the National Cancer Institute, and international partners such as the European Bioinformatics Institute are rapidly growing. The ability to store and compute using these data must therefore be addressed by a combination of local, national, and industry resources that exchange large datasets. Maintaining data-intensive flows that comply with the Health Insurance Portability and Accountability Act (HIPAA) and other regulations presents a new challenge for biomedical research. We describe a strategy that marries performance and security by borrowing from and redefining the concept of a Science DMZ, a framework that is used in physical sciences and engineering research to manage high-capacity data flows. Conclusion By implementing a Medical Science DMZ architecture, biomedical researchers can leverage the scale provided by high-performance computer and cloud storage facilities and national high-speed research networks while preserving privacy and meeting regulatory requirements.

• Sponsoring Organization: USDOE
• OSTI ID: 1779352
• Journal Information: Journal of the American Medical Informatics Association, Journal Name: Journal of the American Medical Informatics Association Vol. 25 Journal Issue: 3; ISSN 1067-5027
• Publisher: Oxford University Press
• Country of Publication: United Kingdom
• Language: English