Recently, with the rapid development of information and communication technologies, the infrastructures, resources, end devices, and applications in communications and networking systems are becoming much more complex and heterogeneous. In addition, the large volume of data and massive end devices may bring serious security, privacy, services provisioning, and network management challenges. In order to achieve decentralized, secure, intelligent, and efficient network operation and management, the joint consideration of blockchain and machine learning (ML) may bring significant benefits and have attracted great interests from both academia and industry. On one hand, blockchain can significantly facilitate training data and ML model sharing, decentralized intelligence, security, privacy, and trusted decision-making of ML. On the other hand, ML will have significant impacts on the development of blockchain in communications and networking systems, including energy and resource efficiency, scalability, security, privacy, and intelligent smart contracts. However, some essential open issues and challenges that remain to be addressed before the widespread deployment of the integration of blockchain and ML, including resource management, data processing, scalable operation, and security issues. In this paper, we present a survey on the existing works for blockchain and ML technologies. We identify several important aspects of integrating blockchain and ML, including overview, benefits, and applications. Then we discuss some open issues, challenges, and broader perspectives that need to be addressed to jointly consider blockchain and ML for communications and networking systems.

中文翻译：

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通信和网络系统的区块链和机器学习

近年来，随着信息和通信技术的快速发展，通信和网络系统中的基础设施、资源、终端设备和应用程序变得更加复杂和异构。此外，海量数据和海量终端设备可能带来严重的安全、隐私、服务提供和网络管理挑战。为了实现去中心化、安全、智能、高效的网络运营管理，区块链和机器学习（ML）的联合考虑可能会带来显着的好处，并引起了学术界和工业界的极大兴趣。一方面，区块链可以显着促进机器学习的训练数据和机器学习模型共享、去中心化智能、安全、隐私和可信决策。另一方面，ML 将对通信和网络系统中区块链的发展产生重大影响，包括能源和资源效率、可扩展性、安全性、隐私和智能智能合约。然而，在广泛部署区块链和机器学习的集成之前，仍有一些重要的开放问题和挑战需要解决，包括资源管理、数据处理、可扩展操作和安全问题。在本文中，我们对区块链和机器学习技术的现有工作进行了调查。我们确定了集成区块链和机器学习的几个重要方面，包括概述、好处和应用程序。然后，我们讨论一些需要解决的开放性问题、挑战和更广泛的观点，以共同考虑将区块链和机器学习用于通信和网络系统。