Experiential Learning Through Immersive XR: Cybersecurity Education for Critical Infrastructures

被引:0
|
作者
Lee, Anthony [1 ]
King, Kenneth [1 ]
Gracanin, Denis [1 ]
Azab, Mohamed [2 ]
机构
[1] Virginia Tech, Blacksburg, VA 24060 USA
[2] Virginia Mil Inst, Lexington, VA 24450 USA
关键词
Artificial Intelligence (AI); Digital Twins; Critical Infrastructures; Cybersecurity; Large Language Models (LLM); Internet of Things (IoT);
D O I
10.1007/978-3-031-61382-1_4
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
with computer systems, critical infrastructures face vulnerability to a variety of cyber-attacks, stemming from the absence of a cybersecurity mindset within these establishments. We need to efficiently educate these workers about the cybersecurity threats that exist, their potential effects, and the subsequent substantial impact on human populations. Previous research has suggested traditional non-interactive training methods are often not effective. We propose an interactive learning experience that incorporates Extended Reality, Digital Twins, and Artificial Intelligence (AI) to help workers become more aware of cybersecurity issues within their critical infrastructure. This paper introduces an innovative testbed that seamlessly integrates Artificial Intelligence (AI) and Large Language Models to create an immersive educational experience. The goal is to effectively convey complex technical concepts to users with limited background knowledge on the subject. Our specific focus lies in addressing the need for proper cybersecurity training among water treatment plant employees. The testbed presented is meticulously crafted to provide users with a tangible representation of the potential outcomes resulting from successful cyber attacks on such facilities. Through this approach, we aim to enhance the educational process and promote a deeper understanding of cybersecurity challenges in critical infrastructure like water treatment plants.
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页码:56 / 69
页数:14
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