Blockchain Based Platform
Blockchain-based platforms are being developed to enhance the security, transparency, and efficiency of various applications, primarily by leveraging the decentralized and immutable nature of blockchain technology. Current research focuses on integrating advanced machine learning models, such as graph neural networks, transformers, and recurrent neural networks, to improve tasks like fraud detection, financial prediction, and secure data sharing in areas like healthcare and IoT. This interdisciplinary field is significant because it addresses critical challenges in data privacy, security, and trust, with potential applications ranging from secure data management in smart cities to verifiable AI model deployment.
Papers
FAIR-BFL: Flexible and Incentive Redesign for Blockchain-based Federated Learning
Rongxin Xu, Shiva Raj Pokhrel, Qiujun Lan, Gang Li
APPFLChain: A Privacy Protection Distributed Artificial-Intelligence Architecture Based on Federated Learning and Consortium Blockchain
Jun-Teng Yang, Wen-Yuan Chen, Che-Hua Li, Scott C. -H. Huang, Hsiao-Chun Wu