Keystroke Dynamics Based Biometric Identification

被引：0

作者：

Boz, Hasan Alp ^{[1
]}

Gurkan, Mert ^{[1
]}

Yanikoglu, Berrin ^{[1
]}

机构：

[1] Sabanci Univ, Tuzla, Turkey

来源：

2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2020年

关键词：

Biometric Identification; Keystroke Dynamics; Attention Mechanism; AUTHENTICATION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Biometrics based keystroke dynamics aim to perform user identification and authentication based on users' typing behaviour on digital devices. In this study, keystroke timing and regional distributions extracted from free-text are utilized to perform user identification. In order to obtain the highest representative set of attributes, attributes based on directional graph, hold time and keyboard distance have been extracted and used in different configurations. In order to process the generated feature sets more effectively, unlike the existing studies, a multilayer artificial neural network model with attention mechanism was used and 0.13% FAR and 2.5% FRR results were obtained.

引用

页数：4

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