Generative AI-enabled Blockchain Networks: Fundamentals, Applications, and Case Study
CoRR(2024)
摘要
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.
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