Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications Article

Aledhari, Mohammed, Razzak, Rehma, Parizi, Reza M et al. (2020). Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications . IEEE ACCESS, 8 140699-140725. 10.1109/ACCESS.2020.3013541

Open Access ESI Most Cited Paper

cited authors

  • Aledhari, Mohammed; Razzak, Rehma; Parizi, Reza M; Saeed, Fahad

sustainable development goals

authors

publication date

  • January 1, 2020

published in

keywords

  • ARTIFICIAL-INTELLIGENCE
  • CHALLENGES
  • Computational modeling
  • Computer Science
  • Computer Science, Information Systems
  • Computer architecture
  • Data models
  • Data privacy
  • Engineering
  • Engineering, Electrical & Electronic
  • Federated learning
  • INTERNET
  • Industries
  • MECHANISM
  • Machine learning
  • PRIVACY
  • Protocols
  • SECURE
  • Science & Technology
  • Technology
  • Telecommunications
  • collaborative AI
  • decentralized data
  • machine learning
  • on-device AI
  • peer-to-peer network
  • privacy
  • security

Digital Object Identifier (DOI)

publisher

  • IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

start page

  • 140699

end page

  • 140725

volume

  • 8