Smartphone passcode prediction

Tao Chen, Michael Farcasin, Eric Chan-Tin
{"title":"Smartphone passcode prediction","authors":"Tao Chen, Michael Farcasin, Eric Chan-Tin","doi":"10.1049/iet-ifs.2017.0606","DOIUrl":null,"url":null,"abstract":"Many people now own smartphones and store all their documents such as pictures and financial statements on their phone. To protect this sensitive information, people generally use a passcode to prevent unauthorised access to their phone. Shoulder-surfing attacks are well known. However, contrary to common belief, they are not easy to carry out. Shoulder-surfing attacks to predict the passcode by humans are shown to not be accurate. The authors thus propose an automated algorithm to accurately predict the passcode entered by a victim on her smartphone by recording the video. Their proposed algorithm is able to predict over 92% of numbers entered in fewer than 75 s with training performed once.","PeriodicalId":13305,"journal":{"name":"IET Inf. Secur.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Inf. Secur.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/iet-ifs.2017.0606","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Many people now own smartphones and store all their documents such as pictures and financial statements on their phone. To protect this sensitive information, people generally use a passcode to prevent unauthorised access to their phone. Shoulder-surfing attacks are well known. However, contrary to common belief, they are not easy to carry out. Shoulder-surfing attacks to predict the passcode by humans are shown to not be accurate. The authors thus propose an automated algorithm to accurately predict the passcode entered by a victim on her smartphone by recording the video. Their proposed algorithm is able to predict over 92% of numbers entered in fewer than 75 s with training performed once.
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
智能手机密码预测
现在很多人都拥有智能手机,并在手机上存储所有文件,如图片和财务报表。为了保护这些敏感信息,人们通常使用密码来防止未经授权的访问他们的手机。肩滑攻击是众所周知的。然而,与普遍的看法相反,它们并不容易执行。通过肩部冲浪攻击来预测人类的密码被证明是不准确的。因此,作者提出了一种自动算法,可以通过录制视频准确预测受害者在智能手机上输入的密码。他们提出的算法能够在75秒内预测超过92%的输入数字,只需进行一次训练。
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
Revisit Two Memoryless State-Recovery Cryptanalysis Methods on A5/1 Improved Lattice-Based Mix-Nets for Electronic Voting Adaptive and survivable trust management for Internet of Things systems Comment on 'Targeted Ciphers for Format-Preserving Encryption' from Selected Areas in Cryptography 2018 Time-specific encrypted range query with minimum leakage disclosure
×
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