Abstract
This paper presents a new feature extraction technique called Pulse Active Mean (PAM) implemented on Electrocardiograms (ECG) for biometric authentication. A doubly secure ECG authentication framework is proposed which makes use of the important attributes of the PAM algorithm as a personal identification number (PIN). The PIN is used to extract different locations of ECG characteristics generating unique feature vectors. The presence of the correct PIN and ECG signals make the proposed authentication framework doubly secure. The performance of PAM is evaluated by comparing its receiver operating characteristic (ROC) curve with traditional temporal and amplitude feature extraction techniques on 100 Physikalisch-Technische Bundesanstalt (PTB) subjects. The evaluation of the biometric performance when different values of PIN are presented is also investigated. It is shown in this paper that different PIN values generate different feature vector sets while still providing consistent authentication performance.
Original language | English |
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Title of host publication | 2011 7th International Conference on Information Assurance and Security (IAS) |
Place of Publication | New York |
Publisher | IEEE |
Pages | 210-214 |
Number of pages | 5 |
ISBN (Print) | 9781457721540 |
DOIs | |
Publication status | Published - 8 Dec 2011 |
Event | 7th International Conference on Information Assurance and Security - Malacca, Malaysia Duration: 5 Dec 2011 → 8 Dec 2011 |
Conference
Conference | 7th International Conference on Information Assurance and Security |
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Country/Territory | Malaysia |
City | Malacca |
Period | 5/12/11 → 8/12/11 |
Keywords
- feature extraction
- vectors
- authentication
- biometrics
- databases
- electrocardiography