ZUO A, FENG Z, PING Y, TAO S, SUN H und CHEN Y, 2026. Fed Graph HE: A privacy-preserving federated graph neural network framework with dynamic homomorphic encryption and robust aggregation. Plo S one. 5 Januar 2026. Vol. 21, no. 1, p. e0339881-e0339881. DOI 10.1371/journal.pone.0339881.
Elsevier - Harvard (with titles)Zuo A, Feng Z, Ping Y, Tao S, Sun H, Chen Y, 2026. Fed Graph HE: A privacy-preserving federated graph neural network framework with dynamic homomorphic encryption and robust aggregation. Plo S one 21, e0339881-e0339881. https://doi.org/10.1371/journal.pone.0339881
American Psychological Association 7th editionZuo A, Feng Z, Ping Y, Tao S, Sun H, & Chen Y. (2026). Fed Graph HE: A privacy-preserving federated graph neural network framework with dynamic homomorphic encryption and robust aggregation. Plo S One, 21(1), e0339881-e0339881. https://doi.org/10.1371/journal.pone.0339881
Springer - Basic (author-date)Zuo A, Feng Z, Ping Y, Tao S, Sun H, Chen Y (2026) Fed Graph HE: A privacy-preserving federated graph neural network framework with dynamic homomorphic encryption and robust aggregation.. Plo S one 21:e0339881-e0339881. https://doi.org/10.1371/journal.pone.0339881
Juristische Zitierweise (Stüber) (Deutsch)Zuo A/ Feng Z/ Ping Y/ Tao S/ Sun H/ Chen Y, Fed Graph HE: A privacy-preserving federated graph neural network framework with dynamic homomorphic encryption and robust aggregation., Plo S one 2026, e0339881-e0339881.