{"title":"基于手势输入生物识别技术的短信隐式作者验证系统","authors":"U. Burgbacher, K. Hinrichs","doi":"10.1145/2556288.2557346","DOIUrl":null,"url":null,"abstract":"Gesture typing is a popular text input method used on smartphones. Gesture keyboards are based on word gestures that subsequently trace all letters of a word on a virtual keyboard. Instead of tapping a word key by key, the user enters a word gesture with a single continuous stroke. In this paper, we introduce an implicit user verification approach for short text messages that are entered with a gesture keyboard. We utilize the way people interact with gesture keyboards to extract behavioral biometric features. We propose a proof-of-concept classification framework that learns the gesture typing behavior of a person and is able to decide whether a gestured message was written by the legitimate user or an imposter. Data collected from gesture keyboard users in a user study is used to assess the performance of the classification framework, demonstrating that the technique has considerable promise.","PeriodicalId":20599,"journal":{"name":"Proceedings of the SIGCHI Conference on Human Factors in Computing Systems","volume":"18 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2014-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"49","resultStr":"{\"title\":\"An implicit author verification system for text messages based on gesture typing biometrics\",\"authors\":\"U. Burgbacher, K. Hinrichs\",\"doi\":\"10.1145/2556288.2557346\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Gesture typing is a popular text input method used on smartphones. Gesture keyboards are based on word gestures that subsequently trace all letters of a word on a virtual keyboard. Instead of tapping a word key by key, the user enters a word gesture with a single continuous stroke. In this paper, we introduce an implicit user verification approach for short text messages that are entered with a gesture keyboard. We utilize the way people interact with gesture keyboards to extract behavioral biometric features. We propose a proof-of-concept classification framework that learns the gesture typing behavior of a person and is able to decide whether a gestured message was written by the legitimate user or an imposter. Data collected from gesture keyboard users in a user study is used to assess the performance of the classification framework, demonstrating that the technique has considerable promise.\",\"PeriodicalId\":20599,\"journal\":{\"name\":\"Proceedings of the SIGCHI Conference on Human Factors in Computing Systems\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"49\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the SIGCHI Conference on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2556288.2557346\",\"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 SIGCHI Conference on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2556288.2557346","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An implicit author verification system for text messages based on gesture typing biometrics
Gesture typing is a popular text input method used on smartphones. Gesture keyboards are based on word gestures that subsequently trace all letters of a word on a virtual keyboard. Instead of tapping a word key by key, the user enters a word gesture with a single continuous stroke. In this paper, we introduce an implicit user verification approach for short text messages that are entered with a gesture keyboard. We utilize the way people interact with gesture keyboards to extract behavioral biometric features. We propose a proof-of-concept classification framework that learns the gesture typing behavior of a person and is able to decide whether a gestured message was written by the legitimate user or an imposter. Data collected from gesture keyboard users in a user study is used to assess the performance of the classification framework, demonstrating that the technique has considerable promise.