A Blockchain Solution for Collaborative Machine Learning over IoT

• URL: http://arxiv.org/abs/2311.14136v1
• Date: Thu, 23 Nov 2023 18:06:05 GMT
• Title: A Blockchain Solution for Collaborative Machine Learning over IoT
• Authors: Carlos Beis-Penedo and Francisco Troncoso-Pastoriza and Rebeca P. D\'iaz-Redondo and Ana Fern\'andez-Vilas and Manuel Fern\'andez-Veiga and Mart\'in Gonz\'alez Soto
• Abstract summary: Federated learning (FL) and blockchain technologies have emerged as promising approaches to address these challenges. We present a novel IoT solution that combines the incremental learning vector quantization algorithm (XuILVQ) with blockchain technology. Our proposed architecture addresses the shortcomings of existing blockchain-based FL solutions by reducing computational and communication overheads while maintaining data privacy and security.
• Score: 0.31410859223862103
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The rapid growth of Internet of Things (IoT) devices and applications has led to an increased demand for advanced analytics and machine learning techniques capable of handling the challenges associated with data privacy, security, and scalability. Federated learning (FL) and blockchain technologies have emerged as promising approaches to address these challenges by enabling decentralized, secure, and privacy-preserving model training on distributed data sources. In this paper, we present a novel IoT solution that combines the incremental learning vector quantization algorithm (XuILVQ) with Ethereum blockchain technology to facilitate secure and efficient data sharing, model training, and prototype storage in a distributed environment. Our proposed architecture addresses the shortcomings of existing blockchain-based FL solutions by reducing computational and communication overheads while maintaining data privacy and security. We assess the performance of our system through a series of experiments, showcasing its potential to enhance the accuracy and efficiency of machine learning tasks in IoT settings.

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