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Blockchain and Machine Learning for Communications and Networking Systems

机译:区块链和机器学习通信和网络系统

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摘要

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.
机译:最近,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,终端设备和应用变得更复杂和异构。此外,大量的数据和大规模的最终设备可能会带来严重的安全性,隐私,服务供应和网络管理挑战。为了实现分散,安全,智能,高效的网络运营和管理,对区间块和机器学习(ML)的联合考虑可能会带来显着的好处,并吸引了学术界和工业的极大兴趣。一方面,区块链可以显着促进培训数据和ML模型共享,分散的智力,安全,隐私和最值得信赖的ML决策。另一方面,ML将对通信和网络系统中区块链产生重大影响,包括能源和资源效率,可扩展性,安全性,隐私和智能智能合同。但是,在广泛部署区块链和ML的集成之前仍有待解决的一些基本开放问题和挑战,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SlowtChain和ML Technologies的现有工作提供了调查。我们确定集成区块链和ML的几个重要方面,包括概述,福利和应用程序。然后,我们讨论了需要解决的一些公开问题,挑战和更广泛的观点,以共同考虑区块链和ML对通信和网络系统。

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