• 3D Beamforming with Massive Cylindrical Arrays for Physical Layer Secure Data Transmission 

      Yaacoub E.; Al-Husseini M.; Chehab A.; Abualsaud K.; Khattab T.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Article)
      In this letter, a novel approach for physical layer security is implemented using massive cylindrical antenna arrays. A part of the arrays is used for transmitting a signal reliably from source to destination using highly ...
    • A secure client-side framework for protecting the privacy of health data stored on the cloud 

      Sakr A.; Yaacoub E.; Noura H.; Al-Husseini M.; Abualsaud K.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      In the past decade, Cloud-Computing emerged as a new computing concept with a distributed nature using virtual network and systems. Many businesses rely on this technology to keep their systems running but concerns are ...
    • A Simple Approach for Securing IoT Data Transmitted over Multi-RATs 

      Diba R.; Yaacoub E.; Al-Husseini M.; Noura H.; Abualsaud K.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      In an mHealth remote patient monitoring scenario, usually control units/data aggregators receive data from the body area network (BAN) sensors then send it to the network or 'cloud'. The control unit would have to transmit ...
    • Classification for Imperfect EEG Epileptic Seizure in IoT applications: A Comparative Study 

      Abualsaud K.; Mohamed A.; Khattab T.; Yaacoub E.; Hasna M.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      Epileptic seizure detection could be detected through investigating the electroencephalography (EEG), which is deemed to be very important for IoT wearable sensor-based health systems. EEG-based classification is crucial ...
    • Combating jamming attacks in multi-channel IoT networks using game theory 

      Guizani M.; Gouissem A.; Abualsaud K.; Yaacoub E.; Khattab T. ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)
      Jamming attacks are among the most widely used techniques to block and disturb legitimate communications. Several techniques are used in the literature to combat these attacks. However, most of them either require the ...
    • Combating jamming attacks in multi-channel IoT networks using game theory 

      Guizani, Mohsen; Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T. ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)
      Jamming attacks are among the most widely used techniques to block and disturb legitimate communications. Several techniques are used in the literature to combat these attacks. However, most of them either require the ...
    • Deep learning and low rank dictionary model for mHealth data 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 ...
    • Drone-SCNet: Scaled Cascade Network for Crowd Counting on Drone Images 

      Elharrouss O.; Almaadeed N.; Abualsaud K.; Al-Ali A.; Mohamed A.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)
      Crowd management is an essential task to ensure the safety and smoothness of any event. Using novel technologies, including surveillance cameras, drones, and the communication techniques between security agents, the control ...
    • Federated Learning Stability Under Byzantine Attacks 

      Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T.; Guizani, M. ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)
      Federated Learning (FL) is a machine learning approach that enables private and decentralized model training. Although FL has been shown to be very useful in several applications, its privacy constraints cause a lack of ...
    • FSC-Set: Counting, Localization of Football Supporters Crowd in the Stadiums 

      Elharrouss O.; Almaadeed N.; Abualsaud K.; Al-Maadeed S.; Al-Ali A.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)
      Counting the number of people in a crowd has gained attention in the last decade. Due to its benefit to many applications such as crowd behavior analysis, crowd management, and video surveillance systems, etc. Counting ...
    • Hybrid Physical Layer Security for Passive RFID Communication 

      Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T.; Guizani, M. ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)
      Thanks to its low cost, small weight and energy efficiency, passive radio frequency identification (RFID) backscatter communications systems have attracted a lot of attention in several application fields. However, such ...
    • Hybrid Physical Layer Security for Passive RFID Communication 

      Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T.; Guizani, M. ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)
      Thanks to its low cost, small weight and energy efficiency, passive radio frequency identification (RFID) backscatter communications systems have attracted a lot of attention in several application fields. However, such ...
    • ICIC-Enabled Association and Channel Selection for UAV-BSS Based on User Locations and Demands 

      Shah S.A.W.; Khafagy M.G.; Khattab T.; Hasna M.O.; Abualsaud K. ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)
      In this work, the downlink association problem is studied when inter-cell interference coordination (ICIC) is enabled at the network side. The serving base stations (BSs) are mounted over unmanned aerial vehicles (UAVs), ...
    • IoT Anti-Jamming Strategy Using Game Theory and Neural Network 

      Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T.; Guizani, M. ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)
      The internet of things (IoT) is one of the most exposed networks to attackers due to its widespread and its heterogeneity. In such networks, jamming attacks are widely used by malicious users to compromise the private and ...
    • IoT Anti-Jamming Strategy Using Game Theory and Neural Network 

      Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T.; Guizani, M. ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)
      The internet of things (IoT) is one of the most exposed networks to attackers due to its widespread and its heterogeneity. In such networks, jamming attacks are widely used by malicious users to compromise the private and ...
    • On the delay of finite buffered multi-hop relay wireless internet of things 

      Elsamadouny A.; Hasna M.; Khattab T.; Abualsaud K.; Yaacoub E. ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)
      The evolution of Internet of Things (IoT) as a new application in wireless networks mandates the utilization of wireless cooperative relaying to overcome the energy limitations of IoT devices. Multi-hop relaying is a ...
    • Performance Comparison of classification algorithms for EEG-based remote epileptic seizure detection in Wireless Sensor Networks 

      Abualsaud K.; Mahmuddin M.; Saleh M.; Mohamed A. ( IEEE Computer Society , 2014 , Conference Paper)
      Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems. Classification is the most important technique for wide-ranging ...
    • Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring 

      Abualsaud K.; Mahmuddin M.; Hussein R.; Mohamed A. ( IEEE , 2013 , Conference Paper)
      Brain is the most important part in the human body controlling muscles and nerves; Electroencephalogram (EEG) signals record brain electric activities. EEG signals capture important information pertinent to different ...
    • Robust Decentralized Federated Learning Using Collaborative Decisions 

      Gouissem, A.; Abualsaud, K.; Yaacoub, E.; Khattab, T.; Guizani, M. ( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference Paper)
      Federated Learning (FL) has attracted a lot of attention in numerous applications due to recent data privacy regulations and increased awareness about data handling issues, combined with the ever-increasing big-data sizes. ...
    • Secure DoF for the MIMO MAC: The case of knowing eavesdropper's channel statistics only 

      Amir M.; Khattab T.; Yaacoub E.; Abualsaud K.; Guizani M. ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)
      Physical layer security has attracted research attention as a means to achieve secure communication without the need for complicated upper layer encryption techniques. The secure degrees of freedom (SDoF) of various networks ...