IoT Authentication Protocols: Challenges, and Comparative Analysis

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Amar Alsheavi, Ammar Hawbani, Wajdy Othman, XINGFU WANG, Gamil Qaid, Liang Zhao, Ahmed Al-Dubai, Liu Zhi, A.S. Ismail, Rutvij Jhaveri, Saeed Alsamhi, Mohammed A. A. Al-qaness
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引用次数: 0

Abstract

In the ever-evolving information technology landscape, the Internet of Things (IoT) is a groundbreaking concept that bridges the physical and digital worlds. It is the backbone of an increasingly sophisticated interactive environment, yet it is a subject of intricate security challenges spawned by its multifaceted manifestations. Central to securing IoT infrastructures is the crucial aspect of authentication, necessitating a comprehensive examination of its nuances, including benefits, challenges, opportunities, trends, and societal implications. In this paper, we thoroughly review the IoT authentication protocols, addressing the main challenges such as privacy protection, scalability, and human factors that may impact security. Through exacting analysis, we evaluate the strengths and weaknesses of existing authentication protocols and conduct a comparative performance analysis to evaluate their effectiveness and scalability in securing IoT environments and devices. At the end of this study, we summarize the main findings and suggest ways to improve the security of IoT devices in the future.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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