深度学习
块链
可追溯性
计算机科学
透明度(行为)
人工智能
数据科学
深度整合
可信赖性
计算机安全
软件工程
业务
国际贸易
作者
Yasir Afaq,Ankush Manocha
标识
DOI:10.1080/08874417.2023.2173330
摘要
ABSTRACTRecently, deep learning and blockchain technologies have gained successful attention due to the high potential of generating accurate decisions and data security, respectively. The data provenances characteristics such as transparency, traceability, and trustworthiness are provided by the vast majority of centralized server-based deep learning approaches. This article examines the advantages of combining deep learning algorithms with blockchain technology. In addition, the most effective strategy for combining these two technologies to achieve the best result is identified through the most recent state-of-the-art literature. In this manner, the article is divided into seven thematic taxonomies based on the literature review: applications of deep learning and blockchain, deep learning techniques, protocols, domains, types of blockchain, and datasets. We have outlined the advantages and disadvantages of blockchain-based deep learning frameworks to facilitate insightful discussions.KEYWORDS: Deep learningblockchainconsensus protocolmachine learningsecurity Disclosure statementNo potential conflict of interest was reported by the author(s).
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