Advancing Collaborative AI Learning Through the Convergence of Blockchain Technology and Federated Learning
- Title
- Advancing Collaborative AI Learning Through the Convergence of Blockchain Technology and Federated Learning
- Creator
- Indoria D.; Parashar J.; Raha S.; Himanshi; Upreti K.; Singh J.
- Description
- Artificial intelligence (AI) has revolutionized multiple sectors through its growth and diversification, notably with the concept of collaborative learning. Among these advancements, federated learning (FL) emerges as a significant decentralized learning approach; however, it is not without its issues. To address the challenges of trust and security in FL, this paper introduces a novel blockchain-based decentralized collaborative learning system and a decentralized asynchronous collaborative learning algorithm for the AI-based industrial Internet environment. We developed a chaincode middleware to bridge blockchain network and AI training for secure, trustworthy and efficient federated learning and presented a refined directed acyclic graph (DAG) consensus mechanism to reduce stale models impact, ensuring efficient learning. Our solutions effectiveness was demonstrated through application on an energy conversion prediction dataset from hydroelectric power generation, validating the practical applicability of our proposed system. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
- Source
- Lecture Notes in Electrical Engineering, Vol-1115, pp. 449-464.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Blockchain technology; Collaborative learning; Decentralized AI systems; Directed acyclic graph (DAG); Federated learning
- Coverage
- Indoria D., Department of Commerce, Vikram Dev University, Jeypore, India; Parashar J., Department of Computer Science and Engineering, Dr. Akhilesh Das Gupta Institute of Technology and Management, Delhi, India; Raha S., Department of Geography, Bhairab Ganguly College, Belgharia, Delhi, India; Himanshi, Department of Information Technology, Raj Kumar Goel Institute of Technology, Ghaziabad, India; Upreti K., Department of Computer Science Technology, CHRIST (Deemed to Be University), Ghaziabad, India; Singh J., School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India
- Rights
- Restricted Access
- Relation
- ISSN: 18761100; ISBN: 978-981998660-6
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Indoria D.; Parashar J.; Raha S.; Himanshi; Upreti K.; Singh J., “Advancing Collaborative AI Learning Through the Convergence of Blockchain Technology and Federated Learning,” CHRIST (Deemed To Be University) Institutional Repository, accessed March 1, 2025, https://archives.christuniversity.in/items/show/19532.