【Author】 Shafay, Muhammad; Ahmad, Raja Wasim; Salah, Khaled; Yaqoob, Ibrar; Jayaraman, Raja; Omar, Mohammed
【Source】CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
【Abstract】Deep learning has gained huge traction in recent years because of its potential to make informed decisions. A large portion of today's deep learning systems are based on centralized servers and fall short in providing operational transparency, traceability, reliability, security, and trusted data provenance features. Also, training deep learning models by utilizing centralized data is vulnerable to the single point of failure problem. In this paper, we explore the importance of integrating blockchain technology with deep learning. We review the existing literature focused on the integration of blockchain with deep learning. We classify and categorize the literature by devising a thematic taxonomy based on seven parameters; namely, blockchain type, deep learning models, deep learning specific consensus protocols, application area, services, data types, and deployment goals. We provide insightful discussions on the state-of-the-art blockchain-based deep learning frameworks by highlighting their strengths and weaknesses. Furthermore, we compare the existing blockchain-based deep learning frameworks based on four parameters such as blockchain type, consensus protocol, deep learning method, and dataset. Finally, we present important research challenges which need to be addressed to develop highly trustworthy deep learning frameworks.
【Keywords】Deep learning; AI; Machine learning; Federated learning; Blockchain; Ethereum; Smart contracts; Security; Transparency
【标题】深度学习的区块链:回顾和开放挑战
【摘要】近年来,深度学习因其做出明智决策的潜力而获得了巨大的关注。当今的深度学习系统中有很大一部分基于集中式服务器,在提供操作透明性、可追溯性、可靠性、安全性和可信数据来源功能方面存在不足。此外,利用集中数据训练深度学习模型容易受到单点故障问题的影响。在本文中,我们探讨了将区块链技术与深度学习相结合的重要性。我们回顾了专注于区块链与深度学习集成的现有文献。我们通过设计基于七个参数的主题分类法对文献进行分类和分类;即区块链类型、深度学习模型、深度学习特定共识协议、应用领域、服务、数据类型和部署目标。我们通过强调其优势和劣势,就最先进的基于区块链的深度学习框架提供有见地的讨论。此外,我们基于区块链类型、共识协议、深度学习方法和数据集等四个参数比较了现有的基于区块链的深度学习框架。最后,我们提出了开发高度可信赖的深度学习框架需要解决的重要研究挑战。
【关键词】深度学习;人工智能;机器学习;联邦学习;区块链;以太坊;智能合约;安全;透明度
【收录时间】2022-07-06
【文献类型】Review; Early Access
【论文大主题】区块链联邦学习
【论文小主题】两者结合
【影响因子】2.303
【翻译者】石东瑛
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