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Machine Learning and Serious Game for Cybersecurity

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Encyclopedia of Machine Learning and Data Science

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Abstract

Machine learning employs software tools from advanced analytics that use statistical algorithms to find patterns in datasets. Cybersecurity is defined as a set of processes, human behavior, and related systems that help safeguard and protect resources against cyber threats. Serious games represent a genre associated with educational value locating the focus on skill practice and entertainment value during exposure, such as strategic planning and understanding complex phenomena. Machine learning and serious gaming can develop automated teaching aids for improving the training of professionals. Serious games can provide an interactive environment where users learn and practice cybersecurity concepts through the game.

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Author information

Authors and Affiliations

  1. Faculty of Business and IT, Ontario Tech University, Oshawa, ON, Canada

    Patrick C. K. Hung, Kamen Kanev & Hidenori Mimura

  2. Research Institute of Electronics, Shizuoka University, Shizuoka, Japan

    Patrick C. K. Hung, Kamen Kanev & Hidenori Mimura

Authors
  1. Patrick C. K. Hung
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  2. Kamen Kanev
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  3. Hidenori Mimura
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Corresponding author

Correspondence to Patrick C. K. Hung .

Editor information

Editors and Affiliations

  1. Clayton, VIC, Australia

    Dinh Phung

  2. Software Engineering, Monash University School of Computer Science &, Melbourne, VIC, Australia

    Geoffrey I. Webb

  3. Engineering (CSE), University of New South Wales School of Computer Science &, Sydney, NSW, Australia

    Claude Sammut

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Hung, P.C.K., Kanev, K., Mimura, H. (2021). Machine Learning and Serious Game for Cybersecurity. In: Phung, D., Webb, G.I., Sammut, C. (eds) Encyclopedia of Machine Learning and Data Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7502-7_993-1

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  • DOI: https://doi.org/10.1007/978-1-4899-7502-7_993-1

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4899-7502-7

  • Online ISBN: 978-1-4899-7502-7

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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