Isaac Griswold-Steiner, Richard Matovu, Abdul Serwadda
{"title":"Handwriting watcher: A mechanism for smartwatch-driven handwriting authentication","authors":"Isaac Griswold-Steiner, Richard Matovu, Abdul Serwadda","doi":"10.1109/BTAS.2017.8272701","DOIUrl":null,"url":null,"abstract":"Despite decades of research on automated handwriting authentication, there is yet to emerge an automated handwriting authentication application that breaks into the mainstream. In this paper, we argue that the burgeoning wearables market holds the key to a practical handwriting authentication app. With potential applications in online education, standardized testing and mobile banking, we present Handwriting Watcher, a mechanism which leverages a wrist-worn sensor-enabled device to authenticate a user's free handwriting. Through experiments capturing a wide range of writing scenarios, we show Handwriting Watcher attains mean error rates as low as 6.56% across the population. Our work represents a promising step towards a market-ready, generalized handwriting authentication system.","PeriodicalId":372008,"journal":{"name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Joint Conference on Biometrics (IJCB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BTAS.2017.8272701","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
Despite decades of research on automated handwriting authentication, there is yet to emerge an automated handwriting authentication application that breaks into the mainstream. In this paper, we argue that the burgeoning wearables market holds the key to a practical handwriting authentication app. With potential applications in online education, standardized testing and mobile banking, we present Handwriting Watcher, a mechanism which leverages a wrist-worn sensor-enabled device to authenticate a user's free handwriting. Through experiments capturing a wide range of writing scenarios, we show Handwriting Watcher attains mean error rates as low as 6.56% across the population. Our work represents a promising step towards a market-ready, generalized handwriting authentication system.