Secure Semantic Communications: Fundamentals and Challenges
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Abstract (arXiv)
Semantic communication allows the receiver to know the intention instead of the bit information itself, which is an emerging technique to support real-time human-machine and machine-to-machine interactions for future wireless communications. In semantic communications, both transmitter and receiver share some common knowledge, which can be used to extract small-size information at the transmitter and recover the original information at the receiver. Due to different design purposes, security issues in semantic communications have two unique features compared to standard bit-wise communications. First, an attacker in semantic communications considers not only the amount of stolen data but also the meanings of stolen data. Second, an attacker in semantic communication systems can attack not only semantic information transmission as done in standard communication systems but also attacks machine learning (ML) models used for semantic information extraction since most of semantic information is generated using ML based methods. Due to these unique features, in this paper, we present an overview on the fundamentals and key challenges in the design of secure semantic communication. We first provide various methods to define and extract semantic information. Then, we focus on secure semantic communication techniques in two areas: information security and semantic ML model security. For each area, we identify the main problems and challenges. Then, we will provide a comprehensive treatment of these problems. In a nutshell,this article provides a holistic set of guidelines on how to design secure semantic communication systems over real-world wireless communication networks.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jan 2023.
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Citing papers per year: 2023: 2; 2024: 1; 2025: 4; 2026: 3.
10 papers.
- 2023Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunitiescited by 4
- 2023CATFL: Certificateless Authentication-based Trustworthy Federated Learning for 6G Semantic Communicationscited by 3
- 2024IRS-Enhanced Secure Semantic Communication Networks: Cross-Layer and Context-Awared Resource Allocationcited by 1
- 2025Deep Learning in Wireless Communication Receiver: A Surveycited by 1
- 2025Diffusion-aided Task-oriented Semantic Communications with Model Inversion Attackcited by 1
- 2026Adaptive Dual-Path Framework for Covert Semantic Communicationcited by 1
- 2025Concealment of Intent: A Game-Theoretic Analysiscited by 0
- 2025Optimization of Private Semantic Communication Performance: An Uncooperative Covert Communication Methodcited by 0
- 2026A Theoretical Game of Attacks via Compositional Skillscited by 0
- 2026Semantic Leakage and Privacy Preservation in Relay-Assisted Semantic Communicationscited by 0
- 2026Semantic Leakage and Privacy Preservation in Relay-Assisted Semantic Communications30 Jun 2026
- 2026Adaptive Dual-Path Framework for Covert Semantic Communication5 May 2026
- 2026A Theoretical Game of Attacks via Compositional Skills1 May 2026
- 2025Optimization of Private Semantic Communication Performance: An Uncooperative Covert Communication Method11 Aug 2025
- 2025Diffusion-aided Task-oriented Semantic Communications with Model Inversion Attack24 Jun 2025
- 2025Concealment of Intent: A Game-Theoretic Analysis27 May 2025
- 2025Deep Learning in Wireless Communication Receiver: A Survey25 Jan 2025
- 2024IRS-Enhanced Secure Semantic Communication Networks: Cross-Layer and Context-Awared Resource Allocation4 Nov 2024
- 2023Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities13 Jul 2023
- 2023CATFL: Certificateless Authentication-based Trustworthy Federated Learning for 6G Semantic Communications1 Feb 2023