arrow
Return

Real-time electrocardiogram streams for continuous authentication

delete2018-07-01
delete38
PRE
AI
C
Carmen Cámara
P
Pedro Peris‐Lopez *
L
Lorena González‐Manzano
J
Juan Tapiador
DOI:10.1016/j.asoc.2017.07.032delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
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.
Keywords:
Datastreams
Healthcare
Identification
Electrocardiogram
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

Organization

A
Aalto University
Scholars:
1.6W
Papers: 1.5W
Citations: 2.1W