Liu, Tian, Hu, Xueyang, Xu, Hairuo, Shu, Tao, and Nguyen, Diep N. High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation. Retrieved from https://par.nsf.gov/biblio/10355175. Journal of Information Security and Applications 70.C Web. doi:10.1016/j.jisa.2022.103309.

Liu, Tian, Hu, Xueyang, Xu, Hairuo, Shu, Tao, & Nguyen, Diep N. High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation. Journal of Information Security and Applications, 70 (C). Retrieved from https://par.nsf.gov/biblio/10355175. https://doi.org/10.1016/j.jisa.2022.103309

Liu, Tian, Hu, Xueyang, Xu, Hairuo, Shu, Tao, and Nguyen, Diep N. "High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation". Journal of Information Security and Applications 70 (C). Country unknown/Code not available. https://doi.org/10.1016/j.jisa.2022.103309. https://par.nsf.gov/biblio/10355175.

@article{osti_10355175,
place = {Country unknown/Code not available}, title = {High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation}, url = {https://par.nsf.gov/biblio/10355175}, DOI = {10.1016/j.jisa.2022.103309}, abstractNote = {}, journal = {Journal of Information Security and Applications}, volume = {70}, number = {C}, author = {Liu, Tian and Hu, Xueyang and Xu, Hairuo and Shu, Tao and Nguyen, Diep N.}, }