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Personalized Cybersecurity Education: A Mobile App Proof of Concept

  • Yusuf Albayram,
  • David Suess,
  • Yassir Yaghzar Elidrissi,
  • Daniel P. Rollins,
  • Maciej Beclawski

摘要

Online users are confronted with many privacy and security decisions every day. However, users often fail to understand online privacy, security risks and the importance of security solutions. Instead of using a “one-size-fits-all” approach in educating people about the security and privacy implications of their technology use to stay safe online as they often vary widely in their level of IT knowledge, personality traits etc., we developed an Android application that provides personalized cybersecurity training using a machine learning algorithm. The app recommends a variety of cybersecurity materials (e.g., videos, articles, tips) for each individual based on their personality traits and IT expertise. The project is a proof of concept, but has the potential to be extended for use by schools, government organizations, and businesses to personalize their cybersecurity training programs.