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Item Applying Rating Systems to Challenge Based Cybersecurity Education(IEEE, 2017-01) Samuels, Andrew; Li, Feng; Justice, Connie; Computer Information and Graphics Technology, School of Engineering and TechnologyAs technology becomes a larger part of everyday life, it becomes increasingly more important for CS and CIT students to learn about cyber security during their education. While many cyber security oriented courses exist, it is also necessary that students must be able to work and learn in an environment that resembles a real world context. To address this problem it has become common to adapt cyber security challenges into the classroom as a method for students to put their knowledge into practice. One problem is that these challenges can vary considerably in levels of difficulty, which makes it problematic for students to be able to select a challenge that is an appropriate difficulty for their skill level. A potential solution to this problem could be to adapt a rating system to rank both the students and the challenges. This would then allow the students to easily select challenges that are appropriate for them to engage with by comparing their own rating with the rating of available challenges. In this project we propose methods that could be used to adapt a rating system to an existing cyber security education program. Finally we propose a method to survey students that interact with the program so that the effect of the rating system can be measured.Item The medical science DMZ: a network design pattern for data-intensive medical science(Oxford University Press, 2018-03-01) Peisert, Sean; Dart, Eli; Barnett, William; Balas, Edward; Cuff, James; Grossman, Robert L.; Berman, Ari; Shankar, Anurag; Tierney, Brian; Medical and Molecular Genetics, School of MedicineAbstract: 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.