HeartPrint: Passive Heart Sounds Authentication Exploiting In-Ear Microphones

Yetong Cao, Chao Cai, Fan Li*, Zhe Chen, Jun Luo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

Biometrics has been increasingly integrated into wearable devices to enhance data privacy and security in recent years. Meanwhile, the popularity of wearables in turn creates a unique opportunity for capturing novel biometrics leveraging various embedded sensing modalities. In this paper, we study a new intracorporal biometrics combining the uniqueness of i) heart motion, ii) bone conduction, and iii) body asymmetry. Specifically, we design HeartPrint as a passive yet secure user authentication system: it exploits the bone-conducted heart sounds captured by (widely available) dual in-ear microphones (IEMs) to authenticate users, while neatly leveraging IEMs renders itself transparent to users without impairing the normal functions of earphones. To suppress the interference from other body sounds and audio produced by the earphones, we develop a novel interference elimination method using modified non-negative matrix factorization to separate clean heart sounds from background interference. We further explore the uniqueness of IEM-recorded heart sounds in three aspects to extract a novel biometric representation, based on which HeartPrint leverages a convolutional neural model equipped with a continual learning method to achieve accurate authentication under drifting body conditions. Extensive experiments with 18 pairs of commercial earphones on 45 participants confirm that HeartPrint can achieve 1.6% FAR and 1.8% FRR, while effectively coping with major attacks, complicated interference, and hardware diversity.

Original languageEnglish
Title of host publicationINFOCOM 2023 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350334142
DOIs
Publication statusPublished - 2023
Event42nd IEEE International Conference on Computer Communications, INFOCOM 2023 - Hybrid, New York City, United States
Duration: 17 May 202320 May 2023

Publication series

NameProceedings - IEEE INFOCOM
Volume2023-May
ISSN (Print)0743-166X

Conference

Conference42nd IEEE International Conference on Computer Communications, INFOCOM 2023
Country/TerritoryUnited States
CityHybrid, New York City
Period17/05/2320/05/23

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