Browsing by Author "Abualsaud K."

Now showing items 21-26 of 26

    • Secure mHealth IoT data transfer from the patient to the hospital: A three-tier approach 

      Yaacoub E.; Abualsaud K.; Khattab T.; Guizani M.; Chehab A. ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Article)
      eHealth and mHealth applications are gaining increasing importance with advances in the IoT and the ubiquity of sensor deployments. Measured IoT mHealth data needs to be captured, transmitted, and stored securely, without ...

    • Securing IoT Cooperative Networks Using Energy Harvesting. 

      Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T.; Guizani, M. ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference Paper)
      An energy efficient and secure Internet of Things (IoT) healthcare system is proposed in this paper. By exploiting spatial diversity, energy harvesting and physical layer security techniques, the proposed approach secures ...

    • Securing IoT Cooperative Networks Using Energy Harvesting. 

      Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T.; Guizani, M. ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference Paper)
      An energy efficient and secure Internet of Things (IoT) healthcare system is proposed in this paper. By exploiting spatial diversity, energy harvesting and physical layer security techniques, the proposed approach secures ...

    • Towards Secure IoT Networks in Healthcare Applications: A Game Theoretic Anti-Jamming Framework 

      Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T.; Guizani, M. ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)
      The internet of Things (IoT) is used to interconnect a massive number of heterogeneous resource constrained smart devices. This makes such networks exposed to various types of malicious attacks. In particular, jamming ...

    • UAV-based Semi-Autonomous Data Acquisition and Classification 

      Said A.B.; Mohamed A.; Elfouly T.; Abualsaud K.; Harras K. ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      In the context of mobile Health (mHealth) applications, data are prone to several sources of contamination which would lead to false interpretation and misleading classification results. In this paper, a robust deep learning ...

    • VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results 

      Du D.; Wen L.; Zhu P.; Fan H.; Hu Q.; ... more authors ( Springer Science and Business Media Deutschland GmbH , 2020 , Conference Paper)
      Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint. However, there are few algorithms focusing ...