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IoT Security Management Using Reinforcement Learning: The Case of Cameroon National Regulatory Compliances

Author

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  • Kum Bertrand Kum

    (The ICT University Cameroon under the mentorship of the University of Buea-Faculty of Information & Communications Technologies-Science of Engineering & Information Sciences.)

  • Dr. Austin Oguejiofor Amaechi

    (The ICT University Cameroon under the mentorship of the University of Buea-Faculty of Information & Communications Technologies-Science of Engineering & Information Sciences.)

  • Prof Tonye Emmanuel

    (The ICT University Cameroon under the mentorship of the University of Buea-Faculty of Information & Communications Technologies-Science of Engineering & Information Sciences.)

  • Prof Mbarika W. Victor

    (The ICT University Cameroon under the mentorship of the University of Buea-Faculty of Information & Communications Technologies-Science of Engineering & Information Sciences.)

Abstract

The increasing adoption of Internet of Things (IoT) devices in Cameroon presents significant security challenges, particularly concerning regulatory compliance. Ensuring secure and adaptive management of IoT systems is critical to mitigating cyber risks while aligning with national regulations. This study investigates the use of Reinforcement Learning (RL) for enhancing IoT security management in Cameroon, with a particular focus on compliance with national cybersecurity regulations (e.g., Law No. 2010/012). Using a Markov Decision Process (MDP), the research defines regulatory-compliant state and action spaces, and trains a Q-learning agent within a simulated IoT environment (CyberBattleSim).

Suggested Citation

  • Kum Bertrand Kum & Dr. Austin Oguejiofor Amaechi & Prof Tonye Emmanuel & Prof Mbarika W. Victor, 2025. "IoT Security Management Using Reinforcement Learning: The Case of Cameroon National Regulatory Compliances," International Journal of Latest Technology in Engineering, Management & Applied Science, International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS), vol. 14(6), pages 973-990, June.
    • Handle: RePEc:bjb:journl:v:14:y:2025:i:6:p:973-990
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