Information Outlook, October 2003

Volume 7, Issue 10https://scholarworks.sjsu.edu/sla_io_2003/1009/thumbnail.jp

Information Outlook, May 2003

Volume 7, Issue 5https://scholarworks.sjsu.edu/sla_io_2003/1004/thumbnail.jp

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

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

Service Level Agreement-based GDPR Compliance and Security assurance in (multi)Cloud-based systems

Compliance with the new European General Data Protection Regulation (Regulation (EU) 2016/679) and security assurance are currently two major challenges of Cloud-based systems. GDPR compliance implies both privacy and security mechanisms definition, enforcement and control, including evidence collection. This paper presents a novel DevOps framework aimed at supporting Cloud consumers in designing, deploying and operating (multi)Cloud systems that include the necessary privacy and security controls for ensuring transparency to end-users, third parties in service provision (if any) and law enforcement authorities. The framework relies on the risk-driven specification at design time of privacy and security level objectives in the system Service Level Agreement (SLA) and in their continuous monitoring and enforcement at runtime.The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644429 and No 780351, MUSA project and ENACT project, respectively. We would also like to acknowledge all the members of the MUSA Consortium and ENACT Consortium for their valuable help

Spectroscopic Analysis in the Virtual Observatory Environment with SPLAT-VO

SPLAT-VO is a powerful graphical tool for displaying, comparing, modifying and analyzing astronomical spectra, as well as searching and retrieving spectra from services around the world using Virtual Observatory (VO) protocols and services. The development of SPLAT-VO started in 1999, as part of the Starlink StarJava initiative, sometime before that of the VO, so initial support for the VO was necessarily added once VO standards and services became available. Further developments were supported by the Joint Astronomy Centre, Hawaii until 2009. Since end of 2011 development of SPLAT-VO has been continued by the German Astrophysical Virtual Observatory, and the Astronomical Institute of the Academy of Sciences of the Czech Republic. From this time several new features have been added, including support for the latest VO protocols, along with new visualization and spectra storing capabilities. This paper presents the history of SPLAT-VO, it's capabilities, recent additions and future plans, as well as a discussion on the motivations and lessons learned up to now.Comment: 15 pages, 6 figures, accepted for publication in Astronomy & Computin

Developing numerical libraries in Java

The rapid and widespread adoption of Java has created a demand for reliable and reusable mathematical software components to support the growing number of compute-intensive applications now under development, particularly in science and engineering. In this paper we address practical issues of the Java language and environment which have an effect on numerical library design and development. Benchmarks which illustrate the current levels of performance of key numerical kernels on a variety of Java platforms are presented. Finally, a strategy for the development of a fundamental numerical toolkit for Java is proposed and its current status is described.Comment: 11 pages. Revised version of paper presented to the 1998 ACM Conference on Java for High Performance Network Computing. To appear in Concurrency: Practice and Experienc