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Machine Learning (ML) analyzes, and processes data and develop patterns. In the case of cybersecurity, it helps to better analyze previous cyber attacks and develop proactive strategy to detect and prevent the security threats. Both ML and cybersecurity are important subjects in computing curriculum, but ML for cybersecurity is not well presented there. We design and develop case-study based portable labware on Google CoLab for ML to cybersecurity so that students can access and practice these hands-on labs anywhere and anytime without time tedious installation and configuration which will help students more focus on learning of concepts and getting more experience for hands-on problem solving skills.
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Colab Cloud Based Portable and Shareable Hands-on Labware for Machine Learning to Cybersecurity
Machine Learning (ML) analyze, and process data and develop patterns. In the case of cybersecurity, it helps to better analyze previous cyber attacks and develop proactive strategy to detect, prevent the security threats. Both ML and cybersecurity are important subjects in computing curriculum but ML for security is not well presented there. We design and develop case-study based portable labware on Google CoLab for ML to cybersecurity so that students can access, share, collaborate, and practice these hands-on labs anywhere and anytime without time tedious installation and configuration which will help students more focus on learning of concepts and getting more experience for hands-on problem solving skills.
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- PAR ID:
- 10346959
- Date Published:
- Journal Name:
- 2021 IEEE International Conference on Big Data (Big Data)
- Page Range / eLocation ID:
- 3311 to 3315
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/BigData52589.2021.9671541
