Abstract
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.
Original language | English |
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Title of host publication | 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT) |
Publisher | IEEE |
Pages | 6-10 |
Number of pages | 5 |
ISBN (Electronic) | 9781728160900 |
ISBN (Print) | 9781728160917 |
Publication status | Published - 4 Aug 2020 |
Event | 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT) - Tartu, Estonia Duration: 6 Jul 2020 → 9 Jul 2020 |
Conference
Conference | 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT) |
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Country/Territory | Estonia |
City | Tartu |
Period | 6/07/20 → 9/07/20 |
Keywords
- cybersecurity
- mOOC
- machine learning
- AI
- systematic literature review
- computer security
- education
- computer aided instruction
- cybersecurity education