K-Medoids-Based Random Biometric Pattern for Cryptographic Key Generation
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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In this paper we present an approach for biometric key generation using wavelets and electrocardiogram (ECG) signals. The stages that comprise the approach are one time enrollment and key derivation. This work is based on the uniqueness and quasi-stationary behavior of ECG signals with respect to an individual. This lets to consider the ECG signal as a biometric characteristic and guarantees that different information is generated and then stored in a token for authentication purposes. Also, this approach implements an error-correction layer using the Hadamard code. The performance of the proposed approach is assessed using ECG signals from MIT-BIH database. Simulation results show a false acceptance rate (FAR) of 4.60 and a false rejection rate (FRR) of 7.90. The random biometric key released by the proposed approach can be used in several encryption algorithms.