Rahbari, D., Daneshtalab, M., Jenihhin, M.

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An efficient architecture for edge AI federated learning with homomorphic encryption

author

Rahbari, Dadmehr

Daneshtalab, Masoud

Jenihhin, Maksim

statement of authorship

Dadmehr Rahbari, Masoud Daneshtalab, Maksim Jenihhin

source

IEEE Access

publisher

IEEE

journal volume number month

vol. 13

year of publication

2025

pages

p. 97919-97929

url

https://doi.org/10.1109/ACCESS.2025.3576689

https://ieeexplore.ieee.org/abstract/document/11023593

subject term

tehisintellekt

tehisõpe

krüptograafia

keyword

edge AI

efficiency

federated learning (FL)

homomorphic encryption

security

ISSN

2169-3536

notes

Bibliogr.: 33 ref

Open Access

scientific publication

teaduspublikatsioon

classifier

1.1

Scopus

Journal metrics at Scopus

Article at Scopus

WOS

Journal metrics at WOS

Article at WOS

category (general)

Tehnika

Arvutiteadus

Materjaliteadus

category (sub)

Tehnika. Üldine inseneriteadus

Arvutiteadus. Üldine arvutiteadus

Materjaliteadus. Üldine materjaliteadus

TalTech department

arvutisüsteemide instituut

language

inglise

Rahbari, D., Daneshtalab, M., Jenihhin, M. An efficient architecture for edge AI federated learning with homomorphic encryption // IEEE Access (2025) vol. 13, p. 97919-97929. https://doi.org/10.1109/ACCESS.2025.3576689 https://ieeexplore.ieee.org/abstract/document/11023593