A Systematic Survey of Blockchained Federated Learning

TL;DR

BCFL addresses the core privacy and scalability challenges of Federated Learning by integrating blockchain to remove central aggregation, enable verification of updates, and provide incentive and data-sharing mechanisms. The paper systematizes BCFL into three architecture types—fully, flexibly, and loosely coupled—and contrasts public versus permissioned blockchains, along with learning devices on end devices and edge nodes. It details four key BCFL functions (verification, aggregation, distributed ledger usage, incentives) and surveys applications in IoT, healthcare, business/finance, and smart city contexts, while outlining challenges in privacy, security, efficiency, and resource use and proposing directions for mobile adoption, Byzantine-robustness, fairness, learning-aware designs, and FL-assisted blockchain. The work serves as a foundational guide for researchers and practitioners to design BCFL systems tailored to specific constraints and goals, facilitating secure, scalable, and auditable distributed learning in real-world deployments.

Abstract

With the technological advances in machine learning, effective ways are available to process the huge amount of data generated in real life. However, issues of privacy and scalability will constrain the development of machine learning. Federated learning (FL) can prevent privacy leakage by assigning training tasks to multiple clients, thus separating the central server from the local devices. However, FL still suffers from shortcomings such as single-point-failure and malicious data. The emergence of blockchain provides a secure and efficient solution for the deployment of FL. In this paper, we conduct a comprehensive survey of the literature on blockchained FL (BCFL). First, we investigate how blockchain can be applied to federal learning from the perspective of system composition. Then, we analyze the concrete functions of BCFL from the perspective of mechanism design and illustrate what problems blockchain addresses specifically for FL. We also survey the applications of BCFL in reality. Finally, we discuss some challenges and future research directions.

Figures (4)

• Figure 1: The topology of FL.
• Figure 2: The topology of fully coupled BCFL.
• Figure 3: The topology of flexibly coupled BCFL.
• Figure 4: The topology of loosely coupled BCFL.