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CATFL: Certificateless Authentication-based Trustworthy Federated Learning for 6G Semantic Communications. (arXiv:2302.00271v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
Federated learning (FL) provides an emerging approach for collaboratively
training semantic encoder/decoder models of semantic communication systems,
without private user data leaving the devices. Most existing studies on
trustworthy FL aim to eliminate data poisoning threats that are produced by
malicious clients, but in many cases, eliminating model poisoning attacks
brought by fake servers is also an important objective. In this paper, a
certificateless authentication-based trustworthy federated learning (CATFL)
framework is proposed, which mutually authenticates the identity of clients and …
aim attacks authentication cases clients communication communications data data poisoning decoder devices emerging fake federated learning important malicious poisoning private servers studies systems threats training user data