A New Solution to the Brain State Permanency for Brain-Based Authentication Methods

Fares Yousefi, H. Kolivand
{"title":"A New Solution to the Brain State Permanency for Brain-Based Authentication Methods","authors":"Fares Yousefi, H. Kolivand","doi":"10.1109/CAIDA51941.2021.9425075","DOIUrl":null,"url":null,"abstract":"Nowadays, to access any digital device we use authentication techniques, which is a critical technology in terms of security. Present biometric authentications such as fingerprints or face recognition are the most used methods in our digitalized world, which are impressively advantageous in terms of security. However, there are still some flaws in using these methods like not being useful for physical disabilities, environment usage matters, and most importantly the possibility of replicating them with some new technologies because of their visibility. Brain signal is another human biometric that could cover the issues of other types in terms of security and visibility. There are different perspectives about the EEG authentication challenges, including ease of use, privacy, and confirmation necessities like comprehensiveness, uniqueness, collectability, and most importantly permanency which is a big challenge for EEG-based authentications specifically. In this paper, we proposed a method using the deep breath strategy to use brain signals for authentication purposes regardless of brain situation. The result shows that our proposal accomplishment can alter the entire cycle of brain-based authentication when compared with other techniques and EEG-based authentication methods according to the parameter of permanency of the technique in many different brain states.","PeriodicalId":272573,"journal":{"name":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAIDA51941.2021.9425075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Nowadays, to access any digital device we use authentication techniques, which is a critical technology in terms of security. Present biometric authentications such as fingerprints or face recognition are the most used methods in our digitalized world, which are impressively advantageous in terms of security. However, there are still some flaws in using these methods like not being useful for physical disabilities, environment usage matters, and most importantly the possibility of replicating them with some new technologies because of their visibility. Brain signal is another human biometric that could cover the issues of other types in terms of security and visibility. There are different perspectives about the EEG authentication challenges, including ease of use, privacy, and confirmation necessities like comprehensiveness, uniqueness, collectability, and most importantly permanency which is a big challenge for EEG-based authentications specifically. In this paper, we proposed a method using the deep breath strategy to use brain signals for authentication purposes regardless of brain situation. The result shows that our proposal accomplishment can alter the entire cycle of brain-based authentication when compared with other techniques and EEG-based authentication methods according to the parameter of permanency of the technique in many different brain states.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于脑的身份验证方法中脑状态持久性的新解决方案
如今,为了访问任何数字设备,我们使用身份验证技术,这是一项关键的安全技术。目前,指纹或面部识别等生物特征认证是我们数字化世界中使用最多的方法,在安全性方面具有令人印象深刻的优势。然而,使用这些方法仍然存在一些缺陷,比如对身体残疾、环境使用问题没有帮助,最重要的是,由于它们的可见性,使用一些新技术可能会复制它们。大脑信号是另一种人类生物识别技术,可以涵盖其他类型的安全性和可见性问题。关于EEG身份验证的挑战有不同的观点,包括易用性、隐私性和确认必要性,如全面性、唯一性、可收集性,最重要的是持久性,这是基于EEG的身份验证面临的一个巨大挑战。在本文中,我们提出了一种使用深呼吸策略的方法,无论大脑情况如何,都可以使用大脑信号进行身份验证。结果表明,根据该技术在许多不同大脑状态下的持久性参数,与其他技术和基于脑电图的认证方法相比,我们提出的成果可以改变基于大脑的认证的整个周期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Melanoma Skin Lesions Classification using Deep Convolutional Neural Network with Transfer Learning A Comparison of Two-Stage Classifier Algorithm with Ensemble Techniques On Detection of Diabetic Retinopathy Predicting Congestive Heart Failure Risk Factors in King Abdulaziz Medical City A Machine Learning Approach Robotics: Biological Hypercomputation and Bio-Inspired Swarms Intelligence AI Support Marketing: Understanding the Customer Journey towards the Business Development
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1