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物联网安全中的生物识别技术:综述

Biometrics for Internet-of-Things Security: A Review.

机构信息

Cyber Security Cooperative Research Centre, Security Research Institute, School of Science, Edith Cowan University, Joondalup, WA 6027, Australia.

School of Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC 3086, Australia.

出版信息

Sensors (Basel). 2021 Sep 14;21(18):6163. doi: 10.3390/s21186163.

DOI:10.3390/s21186163
PMID:34577370
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8472874/
Abstract

The large number of Internet-of-Things (IoT) devices that need interaction between smart devices and consumers makes security critical to an IoT environment. Biometrics offers an interesting window of opportunity to improve the usability and security of IoT and can play a significant role in securing a wide range of emerging IoT devices to address security challenges. The purpose of this review is to provide a comprehensive survey on the current biometrics research in IoT security, especially focusing on two important aspects, authentication and encryption. Regarding authentication, contemporary biometric-based authentication systems for IoT are discussed and classified based on different biometric traits and the number of biometric traits employed in the system. As for encryption, biometric-cryptographic systems, which integrate biometrics with cryptography and take advantage of both to provide enhanced security for IoT, are thoroughly reviewed and discussed. Moreover, challenges arising from applying biometrics to IoT and potential solutions are identified and analyzed. With an insight into the state-of-the-art research in biometrics for IoT security, this review paper helps advance the study in the field and assists researchers in gaining a good understanding of forward-looking issues and future research directions.

摘要

物联网 (IoT) 设备数量众多,需要智能设备和消费者之间进行交互,因此安全性对于 IoT 环境至关重要。生物识别技术为提高物联网的可用性和安全性提供了一个有趣的机会,并且可以在保护各种新兴物联网设备以应对安全挑战方面发挥重要作用。本文的目的是对物联网安全中的当前生物识别技术研究进行全面调查,特别是重点关注身份验证和加密这两个重要方面。在身份验证方面,讨论了当代基于生物特征的物联网身份验证系统,并根据不同的生物特征和系统中使用的生物特征数量对其进行分类。至于加密,本文深入审查和讨论了将生物识别技术与密码学相结合并利用两者为物联网提供增强安全性的生物识别密码系统。此外,还确定并分析了将生物识别技术应用于物联网所带来的挑战和潜在的解决方案。通过深入了解物联网安全中生物识别技术的最新研究,本文有助于推动该领域的研究,并帮助研究人员很好地理解前瞻性问题和未来的研究方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/4ff518cb1ad4/sensors-21-06163-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/ba6136dd977a/sensors-21-06163-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/5289849f574a/sensors-21-06163-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/a79732f9f8da/sensors-21-06163-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/aa1361c5297b/sensors-21-06163-g004a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/4ff518cb1ad4/sensors-21-06163-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/ba6136dd977a/sensors-21-06163-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/5289849f574a/sensors-21-06163-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/a79732f9f8da/sensors-21-06163-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/aa1361c5297b/sensors-21-06163-g004a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62fe/8472874/4ff518cb1ad4/sensors-21-06163-g005.jpg

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A Cancelable Iris- and Steganography-Based User Authentication System for the Internet of Things.
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