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As the Internet of Things (IoT), cloud computing, and 5G networks enable pervasive connectivity, ensuring the security and reliability of data transmission is vital. This study aims to discuss the problems encountered in preventing optical fog caused by bad hardware that may affect the integrity of the system and ensure ease of use of information. We present a new strategy using a two-stage Hidden Markov Model (HMM) to identify and mitigate the risks of these devices. To improve the overall safety of the air in the machine, the model uses a detection method to describe the behavior of optical equipment. Our method successfully detects internal attacks and mitigates them through simulation and validation experiments using IFogSim. This will reduce the number of false positives and increase the efficiency of the network. This research makes a significant contribution to supporting various IoT applications and directly protecting data by promoting improvements in network security in air and cloud environments. Furthermore, the research contributes to advancing Sustainable Development Goals by enhancing cybersecurity measures in IoT and cloud environments, thereby fostering sustainable infrastructure and ensuring resilient and inclusive information and communication technologies.

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Enhancing Security in Optical Fog-Cloud Networks Through Malicious Edge Device Identification

  • 会议论文

  • 发表日期：

    2026年

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  • Kiran Deep Singh,
  • G. L. Saini,
  • Prabh Deep Singh,
  • Deepak Panwar

摘要

As the Internet of Things (IoT), cloud computing, and 5G networks enable pervasive connectivity, ensuring the security and reliability of data transmission is vital. This study aims to discuss the problems encountered in preventing optical fog caused by bad hardware that may affect the integrity of the system and ensure ease of use of information. We present a new strategy using a two-stage Hidden Markov Model (HMM) to identify and mitigate the risks of these devices. To improve the overall safety of the air in the machine, the model uses a detection method to describe the behavior of optical equipment. Our method successfully detects internal attacks and mitigates them through simulation and validation experiments using IFogSim. This will reduce the number of false positives and increase the efficiency of the network. This research makes a significant contribution to supporting various IoT applications and directly protecting data by promoting improvements in network security in air and cloud environments. Furthermore, the research contributes to advancing Sustainable Development Goals by enhancing cybersecurity measures in IoT and cloud environments, thereby fostering sustainable infrastructure and ensuring resilient and inclusive information and communication technologies.