Title
Electromyograph and keystroke dynamics for spoof-resistant biometric authentication
Abstract
Biometrics has come a long way over the past decade in terms of technologies and devices that are used to verify user identities. Three of the more well studied modalities in this field are the face, iris and fingerprint, with the latter two reporting very high user identification/verification rates. In the biometric community there has been little work in studying biomedical signals for user recognition purposes. In this paper, we propose using electromyograph (EMG) signals as a person's biometric signature. The EMG records the motor unit action potentials (MUAP) during any physical motion. Our study is done within the context of a person using a keyboard to type a password or any other fixed phrase. Along with EMG signals, we log key press times for the user and study the feasibility of using this data too as a biometric feature. Keypress timings alone if used as a biometric, are very easy to spoof and hence we fuse this modality with EMG signals. In order to classify these features, we use subspace modeling as well as Bayesian classifiers. The experiments have been performed within the context of a user typing a fixed pass phrase at a workstation. The idea is to monitor both biometric modalities when this action is performed and study user verification across data capture sessions and within capture sessions. Our approach yields high values of verification rates, which shows the promise of using these modalities as user specific biometric signatures.
Year
DOI
Venue
2015
10.1109/CVPRW.2015.7301326
2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Keywords
Field
DocType
electromyograph,keystroke dynamics,spoof-resistant biometric authentication,face modality,iris modality,fingerprint modality,user identification rate,user verification rate,EMG signals,motor unit action potentials,MUAP,biometric feature,subspace modeling,Bayesian classifiers,user specific biometric signatures
Modalities,Computer science,Phrase,Artificial intelligence,Password,Computer vision,Pattern recognition,Keystroke dynamics,Speech recognition,Fingerprint,Feature extraction,Automatic identification and data capture,Biometrics
Conference
Volume
Issue
ISSN
2015
1
2160-7508
Citations 
PageRank 
References 
4
0.39
26
Authors
4
Name
Order
Citations
PageRank
Shreyas Venugopalan1110.98
Felix Juefei-Xu216113.32
Benjamin R Cowley392.35
Marios Savvides41485112.94