网络安全教育中的人工智能——网络安全mooc研究系统文献综述

Samuli Laato, Ali Farooq, H. Tenhunen, Tinja Pitkamaki, Antti Hakkala, A. Airola
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引用次数: 6

摘要

机器学习(ML)技术正在改变网络安全的进攻和防御方面。这对隐私的影响尤其强烈,因为机器学习方法为利用收集的数据提供了前所未有的机会。因此,需要对网络安全和人工智能进行教育。为了研究如何将人工智能和网络安全结合起来进行教学,我们通过系统的文献综述来研究之前关于网络安全mooc的研究。最初的搜索结果是72项,在只筛选了同行评议的网络安全在线课程出版物后,还剩下15项研究。其中3项研究涉及多个网络安全mooc, 12项研究关注单个课程。与所有可用的网络安全mooc相比,评估特定网络安全mooc的已发表作品的数量较少。对研究的分析表明,在几乎所有情况下,网络安全教育都是基于主题而不是使用的工具来组织的,这使得学习者很难找到关于人工智能在网络安全中的应用的重点信息。此外,关于网络安全领域的人工智能应用应如何在在线课程中教授,学术文献中也存在空谈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI in Cybersecurity Education- A Systematic Literature Review of Studies on Cybersecurity MOOCs
Machine learning (ML) techniques are changing both the offensive and defensive aspects of cybersecurity. The implications are especially strong for privacy, as ML approaches provide unprecedented opportunities to make use of collected data. Thus, education on cybersecurity and AI is needed. To investigate how AI and cybersecurity should be taught together, we look at previous studies on cybersecurity MOOCs by conducting a systematic literature review. The initial search resulted in 72 items and after screening for only peer-reviewed publications on cybersecurity online courses, 15 studies remained. Three of the studies concerned multiple cybersecurity MOOCs whereas 12 focused on individual courses. The number of published work evaluating specific cybersecurity MOOCs was found to be small compared to all available cybersecurity MOOCs. Analysis of the studies revealed that cybersecurity education is, in almost all cases, organised based on the topic instead of used tools, making it difficult for learners to find focused information on AI applications in cybersecurity. Furthermore, there is a gab in academic literature on how AI applications in cybersecurity should be taught in online courses.
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