Generative AI-enabled Blockchain Networks: Fundamentals, Applications, and Case Study

Generative Artificial Intelligence (GAI) has recently emerged as a promisingsolution to address critical challenges of blockchain technology, includingscalability, security, privacy, and interoperability. In this paper, we firstintroduce GAI techniques, outline their applications, and discuss existingsolutions for integrating GAI into blockchains. Then, we discuss emergingsolutions that demonstrate the effectiveness of GAI in addressing variouschallenges of blockchain, such as detecting unknown blockchain attacks andsmart contract vulnerabilities, designing key secret sharing schemes, andenhancing privacy. Moreover, we present a case study to demonstrate that GAI,specifically the generative diffusion model, can be employed to optimizeblockchain network performance metrics. Experimental results clearly show that,compared to a baseline traditional AI approach, the proposed generativediffusion model approach can converge faster, achieve higher rewards, andsignificantly improve the throughput and latency of the blockchain network.Additionally, we highlight future research directions for GAI in blockchainapplications, including personalized GAI-enabled blockchains, GAI-blockchainsynergy, and privacy and security considerations within blockchain ecosystems.