Building a Virtual Cybersecurity Collaborative Learning Laboratory (VCCLL)

In fall 2013, the Maine Cybersecurity Cluster (MCSC), was invited to assist the United States Coast Guard with cybersecurity training. MCSC conducted training activities that created the conditions under which Coast Guard personnel could experience and respond to cyber attacks first-hand. A major result of this endeavor was the recognition of two critical needs: 1) the necessity for a flexible, learning laboratory to address the increased security requirements presented by the Internet of Things (IoT), and 2) the need for applied education and training for students going into information assurance professions. To fill these gaps, MCSC designed plans for the creation of a Virtual Cybersecurity Collaborative Learning Lab (VCCLL). The lab would operate inter-institutionally and offer innovative, hands-on, collaborative learning experiences aimed at preventing and mitigating cyber attacks in real time. This paper delineates the background, design, and benefits of the VCCLL

Experiences with Establishment of a Multi-University Center of Academic Excellence in Information Assurance/Cyber Defense

The National Security Agency (NSA) and Department of Homeland Security (DHS), in response to an unmet workforce need for cybersecurity program graduates, jointly sponsor a program by which a post-secondary education institution may achieve recognition as a Center of Academic Excellence in Information Assurance/Cyber Defense (CAE IA/CD). The program identifies standards, criteria, and an evaluation process. Many individual institutions have achieved recognition. The University of Maine System, composed of seven universities, is the first multi-university entity to achieve the CAE IA/CD recognition. The purpose of this paper is to share the key challenges, opportunities, and experiences that contributed to this achievement, and offer recommendations

Influence of the National Trauma Data Bank on the Study of Trauma Outcomes: Is It Time to Set Research Best Practices to Further Enhance Its Impact?

BACKGROUND: Risk-adjusted analyses are critical in evaluating trauma outcomes. The National Trauma Data Bank (NTDB) is a statistically robust registry that allows such analyses; however, analytical techniques are not yet standardized. In this study, we examine peer-reviewed manuscripts published using NTDB data, with particular attention to characteristics strongly associated with trauma outcomes. Our objective is to determine if there are substantial variations in the methodology and quality of risk-adjusted analyses and thus, whether the development of best practices for risk-adjusted analyses is warranted. STUDY DESIGN: A database of all studies utilizing NTDB data published through December 2010 was created by searching Pubmed and Embase. Studies with multivariate risk-adjusted analyses were examined for their central question, main outcome measures, analytical techniques, the co-variates in adjusted analyses, and handling of missing data. RESULTS: Of 286 NTDB publications, 122 performed a multivariable adjusted analysis. These studies focused on Clinical Outcomes (51), Public Health Policy or Injury Prevention (30), Quality (16), Disparities (15), Trauma Center Designation (6) or Scoring Systems (4). Mortality was the main outcome in 98 of these studies. There were considerable differences in the co-variates used for case adjustment. The three most frequently controlled for co-variates were age (95%), Injury Severity Score (85%) and gender (78%). Up to 43% of studies did not control for the five basic covariates necessary to conduct a risk-adjusted analysis of trauma mortality. Less than 10% of studies used clustering to adjust for facility differences or imputation to handle missing data. CONCLUSIONS: There is significant variability in how risk-adjusted analyses using data from the NTDB are performed. Best practices are needed to further improve the quality of research from the NTDB