An empirical study of the inherent resistance of knowledge distillation based federated learning to targeted poisoning attacks

An empirical study of the inherent resistance of knowledge distillation based federated learning to targeted poisoning attacks

While the integration of Knowledge Distillation (KD) into Federated Learning (FL) has recently emerged as a promising solution to address the challenges of heterogeneity and communication efficiency, little is known about the security of these schemes against poisoning attacks prevalent in vanilla F...

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Bibliographic Details
Main Authors: He, Weiyang, Liu, Zizhen, Chang, Chip Hong
Other Authors: School of Electrical and Electronic Engineering
Format: Conference Paper
Language:English
Published: 2024
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Federated Learning
Knowledge Distillation
Backdoor Attacks
Online Access:https://hdl.handle.net/10356/173117

Internet

https://hdl.handle.net/10356/173117

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