Leveraging a cloud-based testbed and software-defined networking for cybersecurity and networking education

被引:3
|
作者
Rahouti, Mohamed [1 ]
Xiong, Kaiqi [2 ,3 ]
Lin, Jing [3 ]
机构
[1] Fordham Univ, Dept Comp & Informat Sci, New York, NY 10023 USA
[2] Univ S Florida, Cyber Florida, Tampa, FL 33620 USA
[3] Univ S Florida, ICNS Lab, Tampa, FL 33620 USA
基金
美国国家科学基金会;
关键词
global environment for network innovations; security; software-defined networking; networking;
D O I
10.1002/eng2.12395
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Nowadays, real-world learning modules become vital components in computer science and engineering in general and cybersecurity in particular. However, as student enrollments have been dramatically increasing, it becomes more challenging for a university/college to keep up with the quality of education that offers hands-on experiment training for students thoroughly. These challenges include the difficulty of providing sufficient computing resources and keep them upgraded for the increasing number of students. In order for higher education institutions to conquer such challenges, some educators introduce an alternative solution. Namely, they develop and deploy virtual lab experiments on the clouds such as Amazon AWS and the Global Environment for Network Innovations (GENI), where students can remotely access virtual resources for lab experiments. Besides, Software-Defined Networks (SDN) are an emerging networking technology to enhance the security and performance of networked communications with simple management. In this article, we present our efforts to develop learning modules via an efficient deployment of SDN on GENI for computer networking and security education. Specifically, we first give our design methodology of the proposed learning modules, and then detail the implementations of the learning modules by starting from user account creation on the GENI testbed to advanced experimental GENI-enabled SDN labs. It is worth pointing out that in order to accommodate students with different backgrounds and knowledge levels, we consider the varying difficulty levels of learning modules in our design. Finally, student assessment over these pedagogical efforts is discussed to demonstrate the efficiency of the proposed learning modules.
引用
收藏
页数:13
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