NeoCyberKG: Enhancing Cybersecurity Laboratories with a Machine Learning-enabled Knowledge Graph

NeoCyberKG: Enhancing Cybersecurity Laboratories with a Machine Learning-enabled Knowledge Graph
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NeoCyber​​KG:通过支持机器学习的知识图增强网络安全实验室

DOI:
10.1145/3430665.3456378
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发表时间:
2021
期刊:
of the 26th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE
影响因子:
--
通讯作者:
Huang, Dijiang
Huang, Dijiang
中科院分区:
--
文献类型:
--
作者:
Deng, Yuli;Zeng, Zhen;Huang, Dijiang

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动手实验是网络安全教育的重要组成部分。缺乏一种连贯的方法来管理现有的实验室,为网络安全领域的学习者提供实用的学习计划。以往的研究利用词嵌入技术构建知识图谱,并以此作为学生的学习指南,但这种方法有其局限性。在本文中,我们提出了一种基于潜在语义分析(LSA)方法的新方法,以取代先前研究中的词嵌入方法,因为它更适合于小规模的语料库,并且它还能够创建一个映射,将每个实验室的主题和每个实验室中包含的概念联系起来。我们使用LSA来识别相关的语义关系,提取相关的实验问题,并从与网络安全主题相关的实验内容中构建知识图。我们利用这项研究的成果,为学生建立一个基于网络的实验室环境:1。提供实验室索引和检索,其中包含每个实验室的概念和知识摘录。2.建立网络安全实验室的推荐/指导系统,根据用户的学习偏好和过去的实验室历史,推荐更多相关的实验室,使学习效果最大化。为了衡量提出的解决方案的有效性,我们进行了一个用例研究,并从一所公立大学的研究生网络安全课程中收集了调查数据。我们的研究表明,通过利用知识图谱作为学习指南,用户倾向于获得更好的学习成果,并对网络安全领域表现出更大的兴趣。
The hands-on lab is a critical component of cybersecurity education. There lacks of a coherent way to manage existing labs to provide a practical learning plan for learners in the cybersecurity area. Previous studies utilized the word embedding technologies to construct a knowledge graph and adopt it as a learning guide for students, but this approach has its limitations. In this paper, we present a new approach based on latent semantic analysis (LSA) method to replace word embedding in previous studies as it is more appropriate in a small-size corpus, and it is also able to create a mapping that connects both the topic of each lab and concepts contained in each lab. We use LSA to identify relevant semantic relations, extract relevant lab problems, and construct knowledge graphs from lab contents related to cybersecurity topics. We utilize the output of this study by establishing a web-based lab environment for students that: 1. providing lab index and searching, which contains concepts and knowledge extract from each lab. 2.building a recommendation/guidance system for cybersecurity labs and suggesting more relevant labs based on users learning preferences and past lab history to maximize learning outcomes. To measure the effectiveness of the proposed solution, we conducted a use case study and collected survey data from a graduate-level cybersecurity class at a public university. Our study shows that users tend to gain enhanced learning outcomes and express more interest in the cybersecurity area by leveraging the knowledge graph as a learning guide.
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DOI: 10.1145/3300115.3309531
发表时间: 2019
期刊: ACM Global Computing Education Conference (CompEd
影响因子: --
作者:
Deng, Yuli;Lu, Duo;Huang, Dijiang;Chung, Chun-Jen;Lin, Fanjie
通讯作者: Lin, Fanjie
DOI: --
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