Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen

The Internet of Things (IoT) technology is rapidly being applied to real life, but the application of a corresponding secure and convenient authentication method is still in significant challenge. So far, pattern, password and fingerprint authentication are the most used methods, but it is important...

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Autores principales:	Jiwoo Lee, Sohyeon Park, Young-Gon Kim, Eun-Kyu Lee, Junghee Jo
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	security authentication IoT wearable device machine learning Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/7b2b07b9f03d4a1787b5ca4bff9d8318
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spelling	oai:doaj.org-article:7b2b07b9f03d4a1787b5ca4bff9d83182021-11-11T15:37:04ZAdvanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen10.3390/electronics102125832079-9292https://doaj.org/article/7b2b07b9f03d4a1787b5ca4bff9d83182021-10-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/21/2583https://doaj.org/toc/2079-9292The Internet of Things (IoT) technology is rapidly being applied to real life, but the application of a corresponding secure and convenient authentication method is still in significant challenge. So far, pattern, password and fingerprint authentication are the most used methods, but it is important to address various security vulnerabilities and limitations of these approaches. In the case of fingerprint recognition, additional hardware such as a fingerprint scanner is required, which causes cost issues and could be vulnerable to fingerprint theft. To solve this problem, this paper proposes a model that uses both biometric and behavioral authentication at the same time. This method exploits the biometric authentication that measures the length of the contact region that occurs when three fingers are placed side by side on the touch screen or pad. In addition, it utilizes the behavioral authentication itself using three-finger L-shape touch, as well as secure geometric information generated by smart watch such as acceleration sensors. Therefore, this proposed model will be useful to implement more secure, rapid and user-friendly way of authentication in many practical busy and buzzling field where deal with sensitive private information.Jiwoo LeeSohyeon ParkYoung-Gon KimEun-Kyu LeeJunghee JoMDPI AGarticlesecurityauthenticationIoTwearable devicemachine learningElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2583, p 2583 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	security authentication IoT wearable device machine learning Electronics TK7800-8360
spellingShingle	security authentication IoT wearable device machine learning Electronics TK7800-8360 Jiwoo Lee Sohyeon Park Young-Gon Kim Eun-Kyu Lee Junghee Jo Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen
description	The Internet of Things (IoT) technology is rapidly being applied to real life, but the application of a corresponding secure and convenient authentication method is still in significant challenge. So far, pattern, password and fingerprint authentication are the most used methods, but it is important to address various security vulnerabilities and limitations of these approaches. In the case of fingerprint recognition, additional hardware such as a fingerprint scanner is required, which causes cost issues and could be vulnerable to fingerprint theft. To solve this problem, this paper proposes a model that uses both biometric and behavioral authentication at the same time. This method exploits the biometric authentication that measures the length of the contact region that occurs when three fingers are placed side by side on the touch screen or pad. In addition, it utilizes the behavioral authentication itself using three-finger L-shape touch, as well as secure geometric information generated by smart watch such as acceleration sensors. Therefore, this proposed model will be useful to implement more secure, rapid and user-friendly way of authentication in many practical busy and buzzling field where deal with sensitive private information.
format	article
author	Jiwoo Lee Sohyeon Park Young-Gon Kim Eun-Kyu Lee Junghee Jo
author_facet	Jiwoo Lee Sohyeon Park Young-Gon Kim Eun-Kyu Lee Junghee Jo
author_sort	Jiwoo Lee
title	Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen
title_short	Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen
title_full	Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen
title_fullStr	Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen
title_full_unstemmed	Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen
title_sort	advanced authentication method by geometric data analysis based on user behavior and biometrics for iot device with touchscreen
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/7b2b07b9f03d4a1787b5ca4bff9d8318
work_keys_str_mv	AT jiwoolee advancedauthenticationmethodbygeometricdataanalysisbasedonuserbehaviorandbiometricsforiotdevicewithtouchscreen AT sohyeonpark advancedauthenticationmethodbygeometricdataanalysisbasedonuserbehaviorandbiometricsforiotdevicewithtouchscreen AT younggonkim advancedauthenticationmethodbygeometricdataanalysisbasedonuserbehaviorandbiometricsforiotdevicewithtouchscreen AT eunkyulee advancedauthenticationmethodbygeometricdataanalysisbasedonuserbehaviorandbiometricsforiotdevicewithtouchscreen AT jungheejo advancedauthenticationmethodbygeometricdataanalysisbasedonuserbehaviorandbiometricsforiotdevicewithtouchscreen
_version_	1718434992309141504

Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen

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