智能手机上的行为生物识别认证框架

Ahmed M. Mahfouz, Tarek M. Mahmoud, A. Eldin
{"title":"智能手机上的行为生物识别认证框架","authors":"Ahmed M. Mahfouz, Tarek M. Mahmoud, A. Eldin","doi":"10.1145/3052973.3055160","DOIUrl":null,"url":null,"abstract":"To protect smartphones from unauthorized access, the user has the option to activate authentication mechanisms : PIN, Password, or Pattern. Unfortunately, these mechanisms are vulnerable to shoulder-surfing, smudge and snooping attacks. Even the traditional biometric based systems such as fingerprint or face, also could be bypassed. In order to protect smartphones data against these sort of attacks, we propose a behavioral biometric authentication framework that leverages the user's behavioral patterns such as touchscreen actions, keystroke, application used and sensor data to authenticate smartphone users. To evaluate the framework, we conducted a field study in which we instrumented the Android OS and collected data from 52 participants during 30-day period. We present the prototype of our framework and we are working on its components to select the best features set that can be used to build different modalities to authenticate users on different contexts. To this end, we developed only one modality, a gesture authentication modality, which authenticate smartphone users based on touch gesture. We evaluated this authentication modality on about 3 million gesture samples based on two schemes, classification scheme with EER~0.004, and anomaly detection scheme with EER~0.10.","PeriodicalId":20540,"journal":{"name":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A Behavioral Biometric Authentication Framework on Smartphones\",\"authors\":\"Ahmed M. Mahfouz, Tarek M. Mahmoud, A. Eldin\",\"doi\":\"10.1145/3052973.3055160\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To protect smartphones from unauthorized access, the user has the option to activate authentication mechanisms : PIN, Password, or Pattern. Unfortunately, these mechanisms are vulnerable to shoulder-surfing, smudge and snooping attacks. Even the traditional biometric based systems such as fingerprint or face, also could be bypassed. In order to protect smartphones data against these sort of attacks, we propose a behavioral biometric authentication framework that leverages the user's behavioral patterns such as touchscreen actions, keystroke, application used and sensor data to authenticate smartphone users. To evaluate the framework, we conducted a field study in which we instrumented the Android OS and collected data from 52 participants during 30-day period. We present the prototype of our framework and we are working on its components to select the best features set that can be used to build different modalities to authenticate users on different contexts. To this end, we developed only one modality, a gesture authentication modality, which authenticate smartphone users based on touch gesture. We evaluated this authentication modality on about 3 million gesture samples based on two schemes, classification scheme with EER~0.004, and anomaly detection scheme with EER~0.10.\",\"PeriodicalId\":20540,\"journal\":{\"name\":\"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3052973.3055160\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3052973.3055160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

为了保护智能手机免遭未经授权的访问,用户可以选择激活身份验证机制:PIN、Password或Pattern。不幸的是,这些机制很容易受到肩部冲浪、涂抹和窥探攻击。即使是传统的基于生物识别的系统,如指纹或面部,也可以被绕过。为了保护智能手机数据免受此类攻击,我们提出了一种行为生物识别认证框架,该框架利用用户的行为模式,如触摸屏操作、击键、使用的应用程序和传感器数据来认证智能手机用户。为了评估该框架,我们进行了一项实地研究,在30天的时间里,我们对Android操作系统进行了检测,并收集了52名参与者的数据。我们展示了框架的原型,并正在对其组件进行研究,以选择可用于构建不同模式的最佳特性集,从而在不同的上下文中对用户进行身份验证。为此,我们只开发了一种模式,即手势认证模式,该模式基于触摸手势对智能手机用户进行认证。基于两种方案,即EER~0.004的分类方案和EER~0.10的异常检测方案,在约300万个手势样本上对该认证模式进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Behavioral Biometric Authentication Framework on Smartphones
To protect smartphones from unauthorized access, the user has the option to activate authentication mechanisms : PIN, Password, or Pattern. Unfortunately, these mechanisms are vulnerable to shoulder-surfing, smudge and snooping attacks. Even the traditional biometric based systems such as fingerprint or face, also could be bypassed. In order to protect smartphones data against these sort of attacks, we propose a behavioral biometric authentication framework that leverages the user's behavioral patterns such as touchscreen actions, keystroke, application used and sensor data to authenticate smartphone users. To evaluate the framework, we conducted a field study in which we instrumented the Android OS and collected data from 52 participants during 30-day period. We present the prototype of our framework and we are working on its components to select the best features set that can be used to build different modalities to authenticate users on different contexts. To this end, we developed only one modality, a gesture authentication modality, which authenticate smartphone users based on touch gesture. We evaluated this authentication modality on about 3 million gesture samples based on two schemes, classification scheme with EER~0.004, and anomaly detection scheme with EER~0.10.
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
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