With the development of communication technologies in 5G networks and the Internet of things (IoT), a massive amount of generated data can improve machine learning (ML) inference through data sharing. However, security and privacy concerns are major obstacles in distributed and wireless networks. In addition, IoT has a limitation on system resources depending on the purpose of services. In addition, a blockchain technology enables secure transactions among participants through consensus algorithms and encryption without a centralized coordinator. In this paper, we first review the federated leaning (FL) and blockchain mechanisms, and then, present a survey on the integration of blockchain and FL for data sharing in industrial, vehicle, and healthcare applications.
翻译:随着通信技术在5G网络和物联网(IoT)的发展,大量生成的数据可以通过数据共享改善机器学习(ML)的推论,然而,安全和隐私问题是分布式和无线网络的主要障碍,此外,IoT根据服务的目的对系统资源有限制,此外,一个连锁技术通过协商一致的算法和加密在没有中央协调员的情况下使参与者之间能够进行安全的交易。在本文件中,我们首先审查联结的倾斜(FL)和阻隔式机制,然后提出关于将块链和FL结合到工业、车辆和保健应用中的数据共享上的调查。