Artificial intelligence in physiological characteristics recognition for internet of things authentication

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外文摘要：Effective user authentication is key to ensuring equipment security,data privacy,and personalized services in Internet of Things(IoT)systems.However,conventional mode-based authentication methods(e.g.,passwords and smart cards)may be vulnerable to a broad range of attacks(e.g.,eavesdropping and side-channel attacks).Hence,there have been attempts to design biometric-based authentication solutions,which rely on physiological and behavioral characteristics.Behavioral characteristics need continuous monitoring and specific environmental settings,which can be challenging to implement in practice.However,we can also leverage Artificial Intelligence(AI)in the extraction and classification of physiological characteristics from IoT devices processing to facilitate authentication.Thus,we review the literature on the use of AI in physiological characteristics recognition pub-lished after 2015.We use the three-layer architecture of the IoT(i.e.,sensing layer,feature layer,and algorithm layer)to guide the discussion of existing approaches and their limitations.We also identify a number of future research opportunities,which will hopefully guide the design of next generation solutions.

外文关键词：

Physiological characteristics recognitionArtificial intelligenceInternet of thingsBiological-driven authentication

作者：

Zhimin Zhang、Huansheng Ning、Fadi Farha、Jianguo Ding、Kim-Kwang Raymond Choo

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作者单位：

School of Computer and Communication Engineering,University of Science and Technology Beijing,Beijing,100083,China

Beijing Engineering Research Center for Cyberspace Data Analysis and Applications,Beijing,100083,China

Faculty of Informatics Engineering,Aleppo University,Aleppo,Syria

Department of Computer Science,Blekinge Institute of Technology,371 79,Karlskrona,Sweden

Department of Information Systems and Cyber Security,University of Texas at San Antonio,San Antonio,TX,78249-0631,USA

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基金：

National Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesCloud Technology Endowed Professorship

项目编号：

61872038FRF-GF-20-15B

出版年：

2024

DOI：

10.1016/j.dcan.2022.10.006

数字通信与网络(英文)

ISSN：

年,卷(期)：2024.10(3)