• BPFL: A Blockchain Based Privacy-Preserving Federated Learning Scheme 

      Wang, Naiyu; Yang, Wenti; Guan, Zhitao; Du, Xiaojiang; Guizani, Mohsen ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference Paper)
      Federated Learning (FL), which allows multiple participants to co-train machine Learning models without exposing local data, has been recognized as a promising method in the past few years. However, in the FL process, the ...
    • 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 ...
    • 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. ...