Dynamic keystroke-password recognition based on piezoelectric-triboelectric coupling sensor array with crosstalk-free for authentication system

IF 16.8 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Nano Energy Pub Date : 2025-01-14 DOI:10.1016/j.nanoen.2025.110667
Wenqiu Liu, Meng Chen, Xiping Jiang, Wei Chen, Seng Zen, Ziyi Ren, Hengyu Guo, Hua Yu
{"title":"Dynamic keystroke-password recognition based on piezoelectric-triboelectric coupling sensor array with crosstalk-free for authentication system","authors":"Wenqiu Liu, Meng Chen, Xiping Jiang, Wei Chen, Seng Zen, Ziyi Ren, Hengyu Guo, Hua Yu","doi":"10.1016/j.nanoen.2025.110667","DOIUrl":null,"url":null,"abstract":"As artificial intelligence technologies progress, Human-Machine Interactions (HMI) must evolve rapidly, necessitating reliable and continuous authentication solutions. We propose dynamic keystroke pattern recognition technology based on a piezoelectric-triboelectric coupling sensor array to address these challenges, enhancing the keystroke signal characteristics. Dual verification technology combining password and biometric authentication effectively enhances the security level of the Human-Machine Interactions system. The triboelectric sensor efficiently reduces the output channels of a 3 × 3 sensing array to a single channel using a mesh topology electrode design. Each of the nine triboelectric sensor units corresponds to nine numeric key, allowing users to input different key combinations that generate unique cryptographic waveforms distinguished by individual keystroke characteristics. A piezoelectric-triboelectric coupling sensor array, structured with multiple layers, is devised. By incorporating a piezoelectric sensor in the upper layer, we harness the complementary effects of piezoelectric and triboelectric properties to boost authentication accuracy and alleviate the limitations of single sensing modalities. Notably, crosstalk is eliminated through the specialized sensor array and the topological electrode design. Integrating the piezoelectric-triboelectric coupling sensor array with a 1D CNN neural network approach achieves password recognition accuracy surpassing 99%, effectively mitigating the risk of password leakage in systems facilitating human-computer interactions.","PeriodicalId":394,"journal":{"name":"Nano Energy","volume":"17 1","pages":""},"PeriodicalIF":16.8000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nano Energy","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1016/j.nanoen.2025.110667","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0

Abstract

As artificial intelligence technologies progress, Human-Machine Interactions (HMI) must evolve rapidly, necessitating reliable and continuous authentication solutions. We propose dynamic keystroke pattern recognition technology based on a piezoelectric-triboelectric coupling sensor array to address these challenges, enhancing the keystroke signal characteristics. Dual verification technology combining password and biometric authentication effectively enhances the security level of the Human-Machine Interactions system. The triboelectric sensor efficiently reduces the output channels of a 3 × 3 sensing array to a single channel using a mesh topology electrode design. Each of the nine triboelectric sensor units corresponds to nine numeric key, allowing users to input different key combinations that generate unique cryptographic waveforms distinguished by individual keystroke characteristics. A piezoelectric-triboelectric coupling sensor array, structured with multiple layers, is devised. By incorporating a piezoelectric sensor in the upper layer, we harness the complementary effects of piezoelectric and triboelectric properties to boost authentication accuracy and alleviate the limitations of single sensing modalities. Notably, crosstalk is eliminated through the specialized sensor array and the topological electrode design. Integrating the piezoelectric-triboelectric coupling sensor array with a 1D CNN neural network approach achieves password recognition accuracy surpassing 99%, effectively mitigating the risk of password leakage in systems facilitating human-computer interactions.

Abstract Image

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
基于压电-摩擦电耦合无串扰传感器阵列的认证系统动态击键-密码识别
随着人工智能技术的进步,人机交互(HMI)必须迅速发展,需要可靠和持续的身份验证解决方案。我们提出了基于压电-摩擦电耦合传感器阵列的动态击键模式识别技术来解决这些挑战,增强击键信号的特性。口令与生物识别相结合的双重验证技术,有效提升了人机交互系统的安全级别。该摩擦电传感器采用网状拓扑电极设计,有效地将3 × 3传感阵列的输出通道减少到单个通道。九个摩擦电传感器单元中的每一个都对应九个数字键,允许用户输入不同的键组合,产生独特的密码波形,由单个按键特征区分。设计了一种多层结构的压电-摩擦耦合传感器阵列。通过在上层集成压电传感器,我们利用压电和摩擦电特性的互补效应来提高认证精度并减轻单一传感模式的局限性。值得注意的是,通过专门的传感器阵列和拓扑电极设计消除了串扰。将压电-摩擦电耦合传感器阵列与一维CNN神经网络方法相结合,密码识别准确率超过99%,有效降低了人机交互系统中密码泄露的风险。
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
Nano Energy
Nano Energy CHEMISTRY, PHYSICAL-NANOSCIENCE & NANOTECHNOLOGY
CiteScore
30.30
自引率
7.40%
发文量
1207
审稿时长
23 days
期刊介绍: Nano Energy is a multidisciplinary, rapid-publication forum of original peer-reviewed contributions on the science and engineering of nanomaterials and nanodevices used in all forms of energy harvesting, conversion, storage, utilization and policy. Through its mixture of articles, reviews, communications, research news, and information on key developments, Nano Energy provides a comprehensive coverage of this exciting and dynamic field which joins nanoscience and nanotechnology with energy science. The journal is relevant to all those who are interested in nanomaterials solutions to the energy problem. Nano Energy publishes original experimental and theoretical research on all aspects of energy-related research which utilizes nanomaterials and nanotechnology. Manuscripts of four types are considered: review articles which inform readers of the latest research and advances in energy science; rapid communications which feature exciting research breakthroughs in the field; full-length articles which report comprehensive research developments; and news and opinions which comment on topical issues or express views on the developments in related fields.
期刊最新文献
Suppression strategy of interfacial defects: γ-ray-induced nano structural rearrangement of NiOx sol-gel for highly sensitive organic photodetectors Magnetoelectric triggered self-powered vital capacity sensor Recent Breakthroughs in Electrocatalytic Reduction of Nitrogen-Oxyanions for Environmentally Benign Ammonia Synthesis An innovative biomimetic technology: Memristors mimic human sensation Boosting contact electro-catalysis efficiency via nano-confinement effect in organic wastewater degradation
×
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