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Title: Training and Teaching Students and IT Professionals on High-throughput Networking and Cybersecurity using a Private Cloud
This paper describes the deployment of a private cloud and the development of virtual laboratories and companion material to teach and train engineering students and Information Technology (IT) professionals in high-throughput networks and cybersecurity. The material and platform, deployed at the University of South Carolina, are also used by other institutions to support regular academic courses, self-pace training of professional IT staff, and workshops across the country. The private cloud is used to deploy scenarios consisting of high-speed networks (up to 50 Gbps), multi-domain environments emulating internetworks, and infrastructures under cyber-attacks using live traffic. For regular academic courses, the virtual laboratories have been adopted by institutions in different states to supplement theoretical material with hands-on activities in IT, electrical engineering, and computer science programs. Topics include Local Area Networks (LANs), congestion-control algorithms, performance tools used to emulate wide area networks (WANs) and their attributes (packet loss, reordering, corruption, latency, jitter, etc.), data transfer applications for high-speed networks, queueing delay and buffer size in routers and switches, active monitoring of multi-domain systems, high-performance cybersecurity tools such as Zeek’s intrusion detection systems, and others. The training platform has been also used by IT professionals from more than 30 states, for self-pace training. The material provides training on topics beyond general-purpose network, which are usually overlooked by practitioners and researchers. The virtual laboratories and companion material have also been used in workshops organized across the country. Workshops are co-organized with organizations that operate large backbone networks connecting research centers and national laboratories, and colleges and universities conducting teaching and research activities.  more » « less
Award ID(s):
1822567
NSF-PAR ID:
10188455
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
2020 Annual Conference of the American Society for Engineering Education
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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