poster

Activity-aware ECG-based patient authentication for remote health monitoring

Authors:

Janani C. Sriram,

Tanzeem Choudhury,

David KotzAuthors Info & Claims

ICMI-MLMI '09: Proceedings of the 2009 international conference on Multimodal interfaces

Pages 297 - 304

https://doi.org/10.1145/1647314.1647378

Published: 02 November 2009 Publication History

Abstract

Mobile medical sensors promise to provide an efficient, accurate, and economic way to monitor patients' health outside the hospital. Patient authentication is a necessary security requirement in remote health monitoring scenarios. The monitoring system needs to make sure that the data is coming from the right person before any medical or financial decisions are made based on the data. Credential-based authentication methods (e.g., passwords, certificates) are not well-suited for remote healthcare as patients could hand over credentials to someone else. Furthermore, one-time authentication using credentials or trait-based biometrics (e.g., face, fingerprints, iris) do not cover the entire monitoring period and may lead to unauthorized post-authentication use. Recent studies have shown that the human electrocardiogram (ECG) exhibits unique patterns that can be used to discriminate individuals. However, perturbation of the ECG signal due to physical activity is a major obstacle in applying the technology in real-world situations. In this paper, we present a novel ECG and accelerometer-based system that can authenticate individuals in an ongoing manner under various activity conditions. We describe the probabilistic authentication system we have developed and present experimental results from 17 individuals.

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Cited By

Bıçakcı HSantopietro MGuest R(2022)Activity‐based electrocardiogram biometric verification using wearable devicesIET Biometrics10.1049/bme2.1210512:1(38-51)Online publication date: 16-Dec-2022
https://doi.org/10.1049/bme2.12105
Wu TYang LMeng QGuo XChen C(2021)Fog-Driven Secure Authentication and Key Exchange Scheme for Wearable Health Monitoring SystemSecurity and Communication Networks10.1155/2021/83686462021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/8368646
Bicakci HSantopietro MBoakes MGuest R(2021)Evaluation of Electrocardiogram Biometric Verification Models Based on Short Enrollment Time on Medical and Wearable Recorders2021 International Carnahan Conference on Security Technology (ICCST)10.1109/ICCST49569.2021.9717372(1-6)Online publication date: 11-Oct-2021
https://doi.org/10.1109/ICCST49569.2021.9717372
Show More Cited By

Index Terms

Activity-aware ECG-based patient authentication for remote health monitoring
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems
2. Security and privacy
  1. Security services
    1. Authentication

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Published In

cover image ACM Conferences

ICMI-MLMI '09: Proceedings of the 2009 international conference on Multimodal interfaces

November 2009

374 pages

ISBN:9781605587721

DOI:10.1145/1647314

General Chairs:
James L. Crowley
INRIA Grenoble Rhône-Alpes Research Centre, France
,
Yuri Ivanov
MERL, USA
,
Christopher Wren
Google, USA
,
Program Chairs:
Daniel Gatica-Perez
Idiap Research Institute, Switzerland
,
Michael Johnston
AT&T Research, USA
,
Rainer Stiefelhagen
University of Karlsruhe, Germany

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

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Published: 02 November 2009

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ICMI-MLMI '09: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERFACES/WORKSHOP ON MACHINE LEARNING FOR MULTIMODAL INTERFACES

November 2 - 4, 2009

Massachusetts, Cambridge, USA

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Cited By

Bıçakcı HSantopietro MGuest R(2022)Activity‐based electrocardiogram biometric verification using wearable devicesIET Biometrics10.1049/bme2.1210512:1(38-51)Online publication date: 16-Dec-2022
https://doi.org/10.1049/bme2.12105
Wu TYang LMeng QGuo XChen C(2021)Fog-Driven Secure Authentication and Key Exchange Scheme for Wearable Health Monitoring SystemSecurity and Communication Networks10.1155/2021/83686462021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/8368646
Bicakci HSantopietro MBoakes MGuest R(2021)Evaluation of Electrocardiogram Biometric Verification Models Based on Short Enrollment Time on Medical and Wearable Recorders2021 International Carnahan Conference on Security Technology (ICCST)10.1109/ICCST49569.2021.9717372(1-6)Online publication date: 11-Oct-2021
https://doi.org/10.1109/ICCST49569.2021.9717372
Uwaechia ARamli D(2021)A Comprehensive Survey on ECG Signals as New Biometric Modality for Human Authentication: Recent Advances and Future ChallengesIEEE Access10.1109/ACCESS.2021.30952489(97760-97802)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3095248
Srivastva RSingh ASingh Y(2021)PlexNet: A fast and robust ECG biometric system for human recognitionInformation Sciences10.1016/j.ins.2021.01.001558(208-228)Online publication date: May-2021
https://doi.org/10.1016/j.ins.2021.01.001
Lehmann FBuschek DBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Heartbeats in the Wild: A Field Study Exploring ECG Biometrics in Everyday LifeProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376536(1-14)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376536
Hosseinzadeh MVo BGhafour MNaghipour S(2020)Electrocardiogram signals-based user authentication systems using soft computing techniquesArtificial Intelligence Review10.1007/s10462-020-09863-0Online publication date: 16-Sep-2020
https://doi.org/10.1007/s10462-020-09863-0
Sonntag D(2019)Medical and health systemsThe Handbook of Multimodal-Multisensor Interfaces10.1145/3233795.3233808(423-476)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1145/3233795.3233808
Lim CWoo WDlay SWu DGao B(2019)Deep Multiview Heartwave AuthenticationIEEE Transactions on Industrial Informatics10.1109/TII.2018.287447715:2(777-786)Online publication date: Feb-2019
https://doi.org/10.1109/TII.2018.2874477
Huang PGuo LLi MFang Y(2019)Practical Privacy-Preserving ECG-Based Authentication for IoT-Based HealthcareIEEE Internet of Things Journal10.1109/JIOT.2019.29290876:5(9200-9210)Online publication date: Oct-2019
https://doi.org/10.1109/JIOT.2019.2929087
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