通过多特征生物识别框架为安全用户访问提供个性化移动电子健康服务

Q2 Nursing
Georgios C. Manikis, M. Spanakis, Emmanouil G Spanakis
{"title":"通过多特征生物识别框架为安全用户访问提供个性化移动电子健康服务","authors":"Georgios C. Manikis, M. Spanakis, Emmanouil G Spanakis","doi":"10.4018/IJRQEH.2019010104","DOIUrl":null,"url":null,"abstract":"Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly available facial images and the efficiency of a prototype version of SpeechXRays, a multi-modal biometric system that uses audio-visual characteristics for user authentication in eHealth platforms. Using the privacy and security mechanism provided, based on audio and video biometrics, medical personnel are able to be verified and subsequently identified for two different eHealth applications. These verified persons are then able to access control, identification, workforce management or patient record storage. In this work, the authors argue how a biometric identification system can greatly benefit healthcare, due to the increased accuracy of identification procedures.","PeriodicalId":36298,"journal":{"name":"International Journal of Reliable and Quality E-Healthcare","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4018/IJRQEH.2019010104","citationCount":"8","resultStr":"{\"title\":\"Personalized Mobile eHealth Services for Secure User Access Through a Multi Feature Biometric Framework\",\"authors\":\"Georgios C. Manikis, M. Spanakis, Emmanouil G Spanakis\",\"doi\":\"10.4018/IJRQEH.2019010104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly available facial images and the efficiency of a prototype version of SpeechXRays, a multi-modal biometric system that uses audio-visual characteristics for user authentication in eHealth platforms. Using the privacy and security mechanism provided, based on audio and video biometrics, medical personnel are able to be verified and subsequently identified for two different eHealth applications. These verified persons are then able to access control, identification, workforce management or patient record storage. In this work, the authors argue how a biometric identification system can greatly benefit healthcare, due to the increased accuracy of identification procedures.\",\"PeriodicalId\":36298,\"journal\":{\"name\":\"International Journal of Reliable and Quality E-Healthcare\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.4018/IJRQEH.2019010104\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Reliable and Quality E-Healthcare\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJRQEH.2019010104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Nursing\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Reliable and Quality E-Healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJRQEH.2019010104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Nursing","Score":null,"Total":0}
引用次数: 8

摘要

人类有各种各样的特征来区分一个人与另一个人,这些特征可以用于识别个人的安全目的。这些生物识别技术可以验证或验证一个人的身份,可以分为两类,生理和行为。在这篇文章中,作者介绍了他们在公开可用的面部图像上的实验结果和语音x射线原型版本的效率,语音x射线是一种多模态生物识别系统,在电子健康平台中使用视听特征进行用户身份验证。利用所提供的基于音频和视频生物识别技术的隐私和安全机制,能够对医务人员进行验证,并随后为两种不同的电子保健应用程序确定身份。然后,这些经过验证的人员能够访问控制、识别、劳动力管理或患者记录存储。在这项工作中,作者认为,由于识别程序的准确性提高,生物识别系统如何极大地有利于医疗保健。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Personalized Mobile eHealth Services for Secure User Access Through a Multi Feature Biometric Framework
Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly available facial images and the efficiency of a prototype version of SpeechXRays, a multi-modal biometric system that uses audio-visual characteristics for user authentication in eHealth platforms. Using the privacy and security mechanism provided, based on audio and video biometrics, medical personnel are able to be verified and subsequently identified for two different eHealth applications. These verified persons are then able to access control, identification, workforce management or patient record storage. In this work, the authors argue how a biometric identification system can greatly benefit healthcare, due to the increased accuracy of identification procedures.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
3.20
自引率
0.00%
发文量
43
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信