Security Perspective of Biometric Recognition and Machine Learning Techniques

Bilgehan Arslan, Ezgi Yorulmaz, Burcin Akca, Ş. Sağiroğlu
{"title":"Security Perspective of Biometric Recognition and Machine Learning Techniques","authors":"Bilgehan Arslan, Ezgi Yorulmaz, Burcin Akca, Ş. Sağiroğlu","doi":"10.1109/ICMLA.2016.0087","DOIUrl":null,"url":null,"abstract":"Biometric systems may be used to create a remote access model on devices, ensure personal data protection, personalize and facilitate the access security. Biometric systems are generally used to increase the security level in addition to the previous authentication methods and they seen as a good solution. Biometry occupies an important place between the areas of daily life of the machine learning. In this study;the techniques, methods, technologies used in biometric systems are researched, machine learning techniques used biometric aplications are investigated for the security perspective, the advantages and disadvantages that these tecniques provide are given. The studies in the literature between 2010-2016 years, used algorithms, technologies, metrics, usage areas, the machine learning techniques used for different biometric systems such as face, palm prints, iris, voice, fingerprint recognition are researched and the studies made are evaluated. The level of security provided by the use of biometric systems by developed using machine learning and disadvantages that arise in the use of these systems are stated in detail in the study. Also, impact on people of biometric methods in terms of ease of use, security and usages areas are examined.","PeriodicalId":356182,"journal":{"name":"2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)","volume":"9 8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLA.2016.0087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

Biometric systems may be used to create a remote access model on devices, ensure personal data protection, personalize and facilitate the access security. Biometric systems are generally used to increase the security level in addition to the previous authentication methods and they seen as a good solution. Biometry occupies an important place between the areas of daily life of the machine learning. In this study;the techniques, methods, technologies used in biometric systems are researched, machine learning techniques used biometric aplications are investigated for the security perspective, the advantages and disadvantages that these tecniques provide are given. The studies in the literature between 2010-2016 years, used algorithms, technologies, metrics, usage areas, the machine learning techniques used for different biometric systems such as face, palm prints, iris, voice, fingerprint recognition are researched and the studies made are evaluated. The level of security provided by the use of biometric systems by developed using machine learning and disadvantages that arise in the use of these systems are stated in detail in the study. Also, impact on people of biometric methods in terms of ease of use, security and usages areas are examined.
生物识别与机器学习技术的安全视角
生物识别系统可用于在设备上创建远程访问模型,确保个人数据保护,个性化和促进访问安全性。生物识别系统通常被用来增加安全级别,除了以前的认证方法,他们被视为一个很好的解决方案。生物计量学在机器学习的日常生活领域之间占有重要的地位。在这项研究中,研究了生物识别系统中使用的技术,方法,技术,从安全角度研究了生物识别应用中的机器学习技术,给出了这些技术提供的优点和缺点。研究了2010-2016年间的文献研究,使用的算法,技术,指标,使用领域,用于不同生物识别系统(如面部,掌纹,虹膜,声音,指纹识别)的机器学习技术,并对所做的研究进行了评估。在研究中详细说明了使用机器学习开发的生物识别系统所提供的安全级别以及使用这些系统所产生的缺点。此外,从易用性、安全性和使用领域分析了生物识别技术对人们的影响。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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