mlsanityData to 7 Oct 2026

Blockchain for Large Language Model Security and Safety: A Holistic Survey

arXiv 2407.20181 ↗First posted 26 Jul 2024cs.CR cs.AI cs.DCcited by 8

On the map: LLM safety and security → Prompt injection and agent security

Abstract (arXiv)

With the growing development and deployment of large language models (LLMs) in both industrial and academic fields, their security and safety concerns have become increasingly critical. However, recent studies indicate that LLMs face numerous vulnerabilities, including data poisoning, prompt injections, and unauthorized data exposure, which conventional methods have struggled to address fully. In parallel, blockchain technology, known for its data immutability and decentralized structure, offers a promising foundation for safeguarding LLMs. In this survey, we aim to comprehensively assess how to leverage blockchain technology to enhance LLMs' security and safety. Besides, we propose a new taxonomy of blockchain for large language models (BC4LLMs) to systematically categorize related works in this emerging field. Our analysis includes novel frameworks and definitions to delineate security and safety in the context of BC4LLMs, highlighting potential research directions and challenges at this intersection. Through this study, we aim to stimulate targeted advancements in blockchain-integrated LLM security.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Placed in Prompt injection and agent security, one of 12 directions in LLM safety and security. Builds on 79 of its 156 references that are in the map. First posted on arXiv 26 Jul 2024.

Builds on

79 of 156 references.

Closest ancestors · 2

Same direction, newest first

  1. 2023Prompt Injection attack against LLM-integrated Applications8 Jun
  2. 2022Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned23 Aug

Other references · 77

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023GPT-4 Technical Reportcited by 18,132
  3. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  4. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,592
  5. 2016Deep Learning with Differential Privacycited by 2,682
  6. 2023A Survey of Large Language Modelscited by 2,537
  7. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  8. 2020RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Modelscited by 1,235
  9. 2023Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversationscited by 1,124
  10. 2023Towards Understanding Sycophancy in Language Modelscited by 988
  11. 2020On Faithfulness and Factuality in Abstractive Summarizationcited by 895
  12. 2023Extracting Training Data from Diffusion Modelscited by 723
38 more
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  2. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
  3. 2023DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Modelscited by 505
  4. 2023Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyondcited by 409
  5. 2023Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignmentcited by 394
  6. 2023A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Uglycited by 380
  7. 2021Membership Inference Attacks on Machine Learning: A Surveycited by 306
  8. 2024TrustLLM: Trustworthiness in Large Language Modelscited by 280
  9. 2023Analyzing Leakage of Personally Identifiable Information in Language Modelscited by 278
  10. 2023Large Language Model Alignment: A Surveycited by 241
  11. 2023"Kelly is a Warm Person, Joseph is a Role Model": Gender Biases in LLM-Generated Reference Letterscited by 196
  12. 2024Foundational Challenges in Assuring Alignment and Safety of Large Language Modelscited by 193
  13. 2023SafetyBench: Evaluating the Safety of Large Language Modelscited by 189
  14. 2023Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attackscited by 189
  15. 2023A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethicscited by 162
  16. 2024The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)cited by 159
  17. 2023Med-HALT: Medical Domain Hallucination Test for Large Language Modelscited by 156
  18. 2023Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritizationcited by 156
  19. 2023Sociotechnical Safety Evaluation of Generative AI Systemscited by 154
  20. 2023ProPILE: Probing Privacy Leakage in Large Language Modelscited by 127
  21. 2024ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teamingcited by 96
  22. 2023A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validationcited by 91
  23. 2024On Protecting the Data Privacy of Large Language Models (LLMs): A Surveycited by 91
  24. 2023Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Modelscited by 87
  25. 2024BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Modelscited by 84
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  27. 2024SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safetycited by 75
  28. 2024JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Modelscited by 67
  29. 2023A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trendscited by 66
  30. 2024TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Modelscited by 63
  31. 2024Pandora: Jailbreak GPTs by Retrieval Augmented Generation Poisoningcited by 62
  32. 2023Privacy Issues in Large Language Models: A Surveycited by 57
  33. 2024Is My Data in Your Retrieval Database? Membership Inference Attacks Against Retrieval Augmented Generationcited by 44
  34. 2021Federated Learning Meets Natural Language Processing: A Surveycited by 42
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  36. 2024Interactive AI with Retrieval-Augmented Generation for Next Generation Networkingcited by 34
  37. 2019Security and Privacy on Blockchaincited by 32
  38. 2023MMST-ViT: Climate Change-aware Crop Yield Prediction via Multi-Modal Spatial-Temporal Vision Transformercited by 29

50 most cited of 77 All 77 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 2.

8 papers.

  1. 2025SoK: Security and Privacy of AI Agents for Blockchaincited by 3
  2. 2024Blockchain Data Analysis in the Era of Large-Language Modelscited by 2
  3. 2025Design and implementation of a distributed security threat detection system integrating federated learning and multimodal LLMcited by 2
  4. 2025DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domaincited by 1
  5. 2025SIEVE: Towards Verifiable Certification for Code-datasetscited by 0
  6. 2025On-Chain Decentralized Learning and Cost-Effective Inference for DeFi Attack Mitigationcited by 0
  7. 2026Trust-Based Incentive Mechanisms in Semi-Decentralized Federated Learning Systemscited by 0
  8. 2026From Network Intrusion Detection to Blockchain-Backed Endpoint Detection and Response: Mapping the Landscape of Decentralized Detection-and-Response Architecturescited by 0