Efficient and secure federated learning against backdoor attacks

• Main Authors: MIAO, Yinbin, XIE, Rongpeng, LI, Xinghua, LIU, Zhiquan, CHOO, Kim-Kwang Raymond, DENG, Robert H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Adaptation models; Adaptive local differential privacy; Artificial neural networks; Backdoor attacks; Compressive sensing; Federated learning; Gaussian noise; Privacy; Servers; Training; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/8660; https://ink.library.smu.edu.sg/context/sis_research/article/9663/viewcontent/Eff_Secure_FL_BackdoorAttacks_av.pdf
• Institution: Singapore Management University

Due to the powerful representation ability and superior performance of Deep Neural Networks (DNN), Federated Learning (FL) based on DNN has attracted much attention from both academic and industrial fields. However, its transmitted plaintext data causes privacy disclosure. FL based on Local Differen...