Malin Eiband, E. V. Zezschwitz, Daniel Buschek, H. Hussmann
{"title":"My Scrawl Hides It All: Protecting Text Messages Against Shoulder Surfing With Handwritten Fonts","authors":"Malin Eiband, E. V. Zezschwitz, Daniel Buschek, H. Hussmann","doi":"10.1145/2851581.2892511","DOIUrl":null,"url":null,"abstract":"We present a novel concept for protecting text messages (e.g. notifications) on mobile devices from shoulder surfing. We propose to display the text in the user's handwriting, assuming that people can read their own handwriting easier and faster than strangers. Our approach was evaluated in a proof-of-concept user study that revealed significant differences in reading time: Participants were indeed slower when reading the unfamiliar handwriting of the other participants compared to their own, and they tended to make more errors. Even though this effect was not present for all participants, we argue that our results may provide the basis for protection mechanisms applicable in real-world scenarios.","PeriodicalId":285547,"journal":{"name":"Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems","volume":"2019 43","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2851581.2892511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
We present a novel concept for protecting text messages (e.g. notifications) on mobile devices from shoulder surfing. We propose to display the text in the user's handwriting, assuming that people can read their own handwriting easier and faster than strangers. Our approach was evaluated in a proof-of-concept user study that revealed significant differences in reading time: Participants were indeed slower when reading the unfamiliar handwriting of the other participants compared to their own, and they tended to make more errors. Even though this effect was not present for all participants, we argue that our results may provide the basis for protection mechanisms applicable in real-world scenarios.