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This content will become publicly available on October 1, 2026

Title: Semantic Edge Computing and Semantic Communications in 6G networks: A unifying survey and research challenges
Award ID(s):
2229472 2134973
PAR ID:
10656187
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
IEEE
Date Published:
Journal Name:
Computer Networks
Volume:
270
Issue:
C
ISSN:
1389-1286
Page Range / eLocation ID:
111531
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  1. Semantic communication is of crucial importance for the next-generation wireless communication networks. The existing works have developed semantic communication frameworks based on deep learning. However, systems powered by deep learning are vulnerable to threats such as backdoor attacks and adversarial attacks. This paper delves into backdoor attacks targeting deep learning-enabled semantic communication systems. Since current works on backdoor attacks are not tailored for semantic communication scenarios, a new backdoor attack paradigm on semantic symbols (BASS) is introduced, based on which the corresponding defense measures are designed. Specifically, a training framework is proposed to prevent BASS. Additionally, reverse engineering-based and pruning-based defense strategies are designed to protect against backdoor attacks in semantic communication. Simulation results demonstrate the effectiveness of both the proposed attack paradigm and the defense strategies. 
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