对智能合约技术中未被发现的漏洞和工具进行系统的文献综述

IF 2.1 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Oualid Zaazaa, Hanan El Bakkali
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引用次数: 0

摘要

近年来,智能合约技术因其解决传统技术长期难以解决的信任问题的能力而引起了广泛关注。然而,就像任何不断发展的技术一样,智能合约也不能幸免于漏洞,有些仍然未被充分开发,通常无法被现有的漏洞评估工具检测到。在本文中,我们对2016 - 2021年间的所有科学研究和论文进行了系统的文献综述。这项工作的主要目标是确定哪些漏洞和智能合约技术尚未得到很好的研究。此外,我们列出了以前研究人员使用的所有数据集,这些数据集可以帮助研究人员在未来构建更有效的机器学习模型。此外,通过考虑各种功能,对智能合约分析工具进行了比较。最后,还讨论了智能合约领域的各种未来方向,可以帮助研究人员为该领域的未来研究设定方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A systematic literature review of undiscovered vulnerabilities and tools in smart contract technology
Abstract In recent years, smart contract technology has garnered significant attention due to its ability to address trust issues that traditional technologies have long struggled with. However, like any evolving technology, smart contracts are not immune to vulnerabilities, and some remain underexplored, often eluding detection by existing vulnerability assessment tools. In this article, we have performed a systematic literature review of all the scientific research and papers conducted between 2016 and 2021. The main objective of this work is to identify what vulnerabilities and smart contract technologies have not been well studied. In addition, we list all the datasets used by previous researchers that can help researchers in building more efficient machine-learning models in the future. In addition, comparisons are drawn among the smart contract analysis tools by considering various features. Finally, various future directions are also discussed in the field of smart contracts that can help researchers to set the direction for future research in this domain.
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来源期刊
Journal of Intelligent Systems
Journal of Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
5.90
自引率
3.30%
发文量
77
审稿时长
51 weeks
期刊介绍: The Journal of Intelligent Systems aims to provide research and review papers, as well as Brief Communications at an interdisciplinary level, with the field of intelligent systems providing the focal point. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. It covers contributions from the social, human and computer sciences to the analysis and application of information technology.
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