A League of Our Own: The Future of Cyber Defense Competitions

Numerous cyber defense competitions exist today for individuals and teams to test their cyber security skills where each team has to “win or go home.” What is missing from these competitions is a league allowing head to head competitions over the course of a season, much like a sport. Teams playing several hours every week during a ten-week season have the opportunity to improve their cyber security skills. This paper provides an overview of cyber security competitions, and how a National Cyber League can greatly expand the number of and participants in these competitions at a much lower cost leveraging virtual technologies

My Student, My Teacher: A Polytechnic Approach to Information Assurance

A polytechnic education involves the practical application of knowledge, including hands-on learning, senior projects, class projects, club activities, professional association activities, and internships. In 1824, the first polytechnic institution in the United States was the Rensselaer School in Troy, New York and today there are approximately 100 polytechnic universities. Several polytechnic institutions are leaders in teaching information assurance. Information assurance educators develop and depend on students to provide leadership in information assurance through active, engaged learning. The goal of this paper is to describe how a polytechnic approach supports information assurance education

Pathway-Based Genomics Prediction using Generalized Elastic Net.

We present a novel regularization scheme called The Generalized Elastic Net (GELnet) that incorporates gene pathway information into feature selection. The proposed formulation is applicable to a wide variety of problems in which the interpretation of predictive features using known molecular interactions is desired. The method naturally steers solutions toward sets of mechanistically interlinked genes. Using experiments on synthetic data, we demonstrate that pathway-guided results maintain, and often improve, the accuracy of predictors even in cases where the full gene network is unknown. We apply the method to predict the drug response of breast cancer cell lines. GELnet is able to reveal genetic determinants of sensitivity and resistance for several compounds. In particular, for an EGFR/HER2 inhibitor, it finds a possible trans-differentiation resistance mechanism missed by the corresponding pathway agnostic approach

CyberPatriot: Exploring University-High School Partnerships

Since its inception in 2008, the CyberPatriot competition has been held annually with the goal of increasing the number of technologically skilled individuals working in the field of cybersecurity. The competition is designed to address the shortage of U.S. citizens with degrees in science, technology, engineering, and math (STEM) disciplines by encouraging talented high school students to pursue post-secondary study leading to careers in cybersecurity. This paper describes how one university successfully partnered with a large metropolitan high school district to better reach out to talented students in both traditional and underrepresented groups

To Catch A Thief II: Computer Forensics in the Classroom

The subject of computer forensics is still new and both challenging and intriguing for students. Cal Poly Pomona has offered this course since September of 2004. The course involves both the technical and legal aspects of investigative procedures as applied to digital evidence. For the instructor, it can involve challenges not found in other areas of information systems. This paper discusses some of the triumphs and pitfalls of including computer forensics as part of an undergraduate information assurance curriculum

Associations of Adiponectin with Adiposity, Insulin Sensitivity, and Diet in Young, Healthy, Mexican Americans and Non-Latino White Adults.

Low circulating adiponectin levels may contribute to higher diabetes risk among Mexican Americans (MA) compared to non-Latino whites (NLW). Our objective was to determine if among young healthy adult MAs have lower adiponectin than NLWs, independent of differences in adiposity. In addition, we explored associations between adiponectin and diet. This was an observational, cross-sectional study of healthy MA and NLW adults living in Colorado (U.S.A.). We measured plasma total adiponectin, adiposity (BMI, and visceral adipose tissue), insulin sensitivity (IVGTT), and self-reported dietary intake in 43 MA and NLW adults. Mean adiponectin levels were 40% lower among MA than NLW (5.8 ± 3.3 vs. 10.7 ± 4.2 µg/mL, p = 0.0003), and this difference persisted after controlling for age, sex, BMI, and visceral adiposity. Lower adiponectin in MA was associated with lower insulin sensitivity (R² = 0.42, p < 0.01). Lower adiponectin was also associated with higher dietary glycemic index, lower intake of vegetables, higher intake of trans fat, and higher intake of grains. Our findings confirm that ethnic differences in adiponectin reflect differences in insulin sensitivity, but suggest that these are not due to differences in adiposity. Observed associations between adiponectin and diet support the need for future studies exploring the regulation of adiponectin by diet and other environmental factors

Supervised and unsupervised language modelling in Chest X-Ray radiological reports

Chest radiography (CXR) is the most commonly used imaging modality and deep neural network (DNN) algorithms have shown promise in effective triage of normal and abnormal radiograms. Typically, DNNs require large quantities of expertly labelled training exemplars, which in clinical contexts is a major bottleneck to effective modelling, as both considerable clinical skill and time is required to produce high-quality ground truths. In this work we evaluate thirteen supervised classifiers using two large free-text corpora and demonstrate that bi-directional long short-term memory (BiLSTM) networks with attention mechanism effectively identify Normal, Abnormal, and Unclear CXR reports in internal (n = 965 manually-labelled reports, f1-score = 0.94) and external (n = 465 manually-labelled reports, f1-score = 0.90) testing sets using a relatively small number of expert-labelled training observations (n = 3,856 annotated reports). Furthermore, we introduce a general unsupervised approach that accurately distinguishes Normal and Abnormal CXR reports in a large unlabelled corpus. We anticipate that the results presented in this work can be used to automatically extract standardized clinical information from free-text CXR radiological reports, facilitating the training of clinical decision support systems for CXR triage