Federated Learning and Blockchain: A Cross-Domain Convergence

Title

Federated Learning and Blockchain: A Cross-Domain Convergence

Creator

Sharma S.; Pandey A.; Sharma V.; Mishra S.; Alkhayyat A.

Description

Gaining significant attention within decentralized contexts, Federated Learning (FL) has been positioned as a highly desirable method for machine learning. By enabling multiple entities to train a shared model cooperatively, data privacy and security are preserved by Federated Learning. Harnessing inherent transparency and accountability of blockchain technology to trace and authenticate updates effectively in federated learning has transpired as an up-and-coming avenue to tackle data challenges related to confidentiality, protection, and reliability. This study examines the viability of federated learning and blockchain integration across multiple dimensions. The technological components of this integration., including incentive systems, consensus mechanisms, data validation, and smart contracts, are delved into. In the study, a novel proposed model for federated learning integrated with blockchain is designed and implemented. It is observed that the mean cypher size is 100 bytes for varying values of gradients. The average throughput recorded is 1.7 bytes per second, while the mean accuracy is 87.1% for 50 epochs. 2023 IEEE.

Source

Proceedings - International Conference on Technological Advancements in Computational Sciences, ICTACS 2023, pp. 1121-1127.

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

blockchain; consensus protocols; Federated learning; machine learning; smart contracts

Coverage

Sharma S., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Pandey A., Oriental Institute of Science and Technology, Madhya Pradesh, Bhopal, India; Sharma V., Christ (Deemed to Be University), Delhi NCR, India; Mishra S., Christ (Deemed to Be University), Delhi NCR, India, Kalinga Institute of Industrial Technology, Deemed to Be University, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq

Rights

Restricted Access

Relation

ISBN: 979-835034233-8

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICTACS59847.2023.10390227

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185386871&doi=10.1109%2fICTACS59847.2023.10390227&partnerID=40&md5=d638a49d0fd38d2bf13e4e77e3e8a321