mlsanityData to 7 Oct 2026

Blockchain-aided Secure Semantic Communication for AI-Generated Content in Metaverse

arXiv 2301.11289 ↗First posted 25 Jan 2023cs.CR cs.CYcited by 15

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Abstract (arXiv)

The construction of virtual transportation networks requires massive data to be transmitted from edge devices to Virtual Service Providers (VSP) to facilitate circulations between the physical and virtual domains in Metaverse. Leveraging semantic communication for reducing information redundancy, VSPs can receive semantic data from edge devices to provide varied services through advanced techniques, e.g., AI-Generated Content (AIGC), for users to explore digital worlds. But the use of semantic communication raises a security issue because attackers could send malicious semantic data with similar semantic information but different desired content to break Metaverse services and cause wrong output of AIGC. Therefore, in this paper, we first propose a blockchain-aided semantic communication framework for AIGC services in virtual transportation networks to facilitate interactions of the physical and virtual domains among VSPs and edge devices. We illustrate a training-based targeted semantic attack scheme to generate adversarial semantic data by various loss functions. We also design a semantic defense scheme that uses the blockchain and zero-knowledge proofs to tell the difference between the semantic similarities of adversarial and authentic semantic data and to check the authenticity of semantic data transformations. Simulation results show that the proposed defense method can reduce the semantic similarity of the adversarial semantic data and the authentic ones by up to 30% compared with the attack scheme.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Jan 2023.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 9; 2024: 3; 2025: 1; 2026: 2.

15 papers.

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  1. 2023Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimizationcited by 56
  2. 2023Zero-Knowledge Proof-based Verifiable Decentralized Machine Learning in Communication Network: A Comprehensive Surveycited by 18
  3. 2024Generative AI for the Optimization of Next-Generation Wireless Networks: Basics, State-of-the-Art, and Open Challengescited by 14
  4. 2023An Overview on Generative AI at Scale with Edge-Cloud Computingcited by 9
  5. 2023UniG3D: A Unified 3D Object Generation Datasetcited by 4
  6. 2023Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunitiescited by 4
  7. 2023BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Modelscited by 4
  8. 2023Privacy Preservation in Artificial Intelligence and Extended Reality (AI-XR) Metaverses: A Surveycited by 3
  9. 2023Secure Deep Reinforcement Learning for Dynamic Resource Allocation in Wireless MEC Networkscited by 2
  10. 2024Detecting AI Generated Text Based on NLP and Machine Learning Approachescited by 2
  11. 2023A Survey of Blockchain, Artificial Intelligence, and Edge Computing for Web 3.0cited by 1
  12. 2024Personalized Federated Learning for Generative AI-Assisted Semantic Communicationscited by 1
3 more
  1. 2025Optimization of Private Semantic Communication Performance: An Uncooperative Covert Communication Methodcited by 0
  2. 2026SoK: A Systematic Bidirectional Literature Review of AI & DLT Convergencecited by 0
  3. 2026Generative AI and Digital Ecosystem Resilience: A Proactive Lifecycle-Based Surveycited by 0