Real-time electrocardiogram streams for continuous authentication

被引:34
|
作者
Camara, Carmen [1 ]
Peris-Lopez, Pedro [1 ,2 ]
Gonzalez-Manzano, Lorena [1 ]
Tapiador, Juan [1 ]
机构
[1] Carlos III Univ Madrid, Avda Univ 30, Leganes 28911, Spain
[2] Aalto Univ, Konemiehentie 2, Espoo 02150, Finland
关键词
Datastreams; Healthcare; Identification; Electrocardiogram; ECG BIOMETRIC RECOGNITION;
D O I
10.1016/j.asoc.2017.07.032
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Security issues are becoming critical in modern smart systems. Particularly, ensuring that only legitimate users get access to them is essential. New access control systems must rely on continuous authentication (CA) to provide higher security level. To achieve this, recent research has shown how biological signals, such as electroencephalograms (EEGs) or electrocardiograms (ECGs), can be useful for this purpose. In this paper, we introduce a new CA scheme that, contrarily to previous works in this area, considers ECG signals as continuous data streams. The data stream paradigm is suitable for this scenario since algorithms tailored for data streams can cope with continuous data of a theoretical infinite length and with a certain variability. The proposed ECG-based CA system is intended for real-time applications and is able to offer an accuracy up to 96%, with an almost perfect system performance (kappa statistic >80%). (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:784 / 794
页数:11
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