Generative AI-enabled Blockchain Networks: Fundamentals, Applications, and Case Study
Not on the map. Why?
Abstract (arXiv)
Generative Artificial Intelligence (GAI) has recently emerged as a promising solution to address critical challenges of blockchain technology, including scalability, security, privacy, and interoperability. In this paper, we first introduce GAI techniques, outline their applications, and discuss existing solutions for integrating GAI into blockchains. Then, we discuss emerging solutions that demonstrate the effectiveness of GAI in addressing various challenges of blockchain, such as detecting unknown blockchain attacks and smart contract vulnerabilities, designing key secret sharing schemes, and enhancing privacy. Moreover, we present a case study to demonstrate that GAI, specifically the generative diffusion model, can be employed to optimize blockchain network performance metrics. Experimental results clearly show that, compared to a baseline traditional AI approach, the proposed generative diffusion model approach can converge faster, achieve higher rewards, and significantly improve the throughput and latency of the blockchain network. Additionally, we highlight future research directions for GAI in blockchain applications, including personalized GAI-enabled blockchains, GAI-blockchain synergy, and privacy and security considerations within blockchain ecosystems.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 17 references that are in the map. First posted on arXiv 28 Jan 2024.
Builds on
8 of 17 references.
References · 8
- 2023Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Servicescited by 76
- 2023Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimizationcited by 56
- 2023Do you still need a manual smart contract audit?cited by 35
- 2023Blockchain Large Language Modelscited by 17
- 2019A Survey of Distributed Consensus Protocols for Blockchain Networkscited by 16
- 2023Generative AI for Cyber Threat-Hunting in 6G-enabled IoT Networkscited by 9
- 2021Deep Transfer Learning: A Novel Collaborative Learning Model for Cyberattack Detection Systems in IoT Networkscited by 2
- 2020Effective Scaling of Blockchain Beyond Consensus Innovations and Moore's Lawcited by 1
Built on by
Citing papers per year: 2024: 1.
1 paper.
Similar, not cited
Close in wording, no citation either way
- 2023From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks
- 2026Blockchain and AI: Securing Intelligent Networks for the Future
- 2026Blockchain-Enabled Artificial Intelligence and AI Agents for Secure Data Sharing and Cybersecurity Applications
- 2026Autonomous Agents on Blockchains: Standards, Execution Models, and Trust Boundaries
- 2024Generative AI for Secure Physical Layer Communications: A Survey
- 2024Graph Attention Network-based Block Propagation with Optimal AoI and Reputation in Web 3.0
- 2024Proof of Quality: A Costless Paradigm for Trustless Generative AI Model Inference on Blockchains
- 2025Efficient and Trustworthy Block Propagation for Blockchain-enabled Mobile Embodied AI Networks: A Graph Resfusion Approach