High-Scalable and Secure Blockchain: Generative Artificial Intelligence as A Key Enabler

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Authors: Xiaoyuan Fu, Wenhao Liu, Quan Sheng Yuan, Yinqiu Liu, Ruichen Zhang, Dusit Niyato, Jiawen Kang, Yi-Xiang Wang
Cited by: 1

Abstract

Blockchain has gained increasing attention as a promising technology for reliable communication and secure collaboration in various fields. However, deploying blockchain in communication systems remains challenging due to its limited performance and large costs. To address this challenge, we propose blockchain generative intelligence (BGI) to enhance both scalability and security of blockchain-based communication systems. Firstly, we introduce the three-level optimization for blockchain enhancement. Based on this, we introduce how to leverage Generative AI (GenAI) to address the scalability and security issues within the three levels of blockchain optimization. Furthermore, in the BGI framework, we incorporate existing blockchain scaling strategies and utilize the advantages of GenAI to mitigate the challenges faced by these scaling strategies, including directed acyclic graph (DAG), sharding, protocol optimization and cross-chain technology. Moreover, we conduct a case study demonstrating the effectiveness of deploying BGI-assisted sharding blockchain in autonomous vehicle platooning (AVP), as one of the promising application scenarios of blockchain. Finally, we evaluate the performance of the proposed strategies by simulations.

Fields of Study & Subjects

Blockchain Technology Applications and Security Vehicular Ad Hoc Networks (VANETs) IoT and Edge/Fog Computing

Publication details

Journal / source
IEEE Wireless Communications
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Pages
1–8
Publication date
1 January 2026
Language
EN