• FEDGAN-IDS: Privacy-preserving IDS using GAN and Federated Learning 

      Aliya, Tabassum; Erbad, Aiman; Lebda, Wadha; Mohamed, Amr; Guizani, Mohsen ( Elsevier , 2022 , Article)
      Federated Learning (FL) is a promising distributed training model that aims to minimize the data sharing to enhance privacy and performance. FL requires sufficient and diverse training data to build efficient models. Lack ...
    • RL-Based Federated Learning Framework Over Blockchain (RL-FL-BC) 

      Riahi, Ali; Mohamed, Amr; Erbad, Aiman ( IEEE , 2023 , Article)
      Federated learning (FL) paradigms aim to amalgamate diverse data properties stored locally at each user, while preserving data privacy through sharing users’ learning experiences and iteratively aggregating their ...