Improving static audio keystroke analysis by score fusion of acoustic and timing data

被引：0

作者：

Matúš Pleva

Patrick Bours

Stanislav Ondáš

Jozef Juhár

机构：

[1] Technical University of Košice,

[2] Department of Electronics and Multimedia Communications,undefined

[3] FEI,undefined

[4] NISlab - Norwegian Information Security Laboratory,undefined

[5] Department of Information Security and Communication Technology,undefined

来源：

Multimedia Tools and Applications | 2017年 / 76卷

关键词：

Biometrics; Keystroke dynamics; Timing analysis; Acoustical analysis; Authentication; Identification;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In this paper we investigate the capacity of sound & timing information during typing of a password for the user identification and authentication task. The novelty of this paper lies in the comparison of performance between improved timing-based and audio-based keystroke dynamics analysis and the fusion for the keystroke authentication. We collected data of 50 people typing the same given password 100 times, divided into 4 sessions of 25 typings and tested how well the system could recognize the correct typist. Using fusion of timing (9.73%) and audio calibration scores (8.99%) described in the paper we achieved 4.65% EER (Equal Error Rate) for the authentication task. The results show the potential of using Audio Keystroke Dynamics information as a way to authenticate or identify users during log-on.

引用

页码：25749 / 25766

页数：17