H. A. Garcia-Baleon, V. Alarcón-Aquino, O. Starostenko
{"title":"A wavelet-based 128-bit key generator using electrocardiogram signals","authors":"H. A. Garcia-Baleon, V. Alarcón-Aquino, O. Starostenko","doi":"10.1109/MWSCAS.2009.5236010","DOIUrl":null,"url":null,"abstract":"In this paper, we present a wavelet-based 128-bit key generator using electrocardiogram (ECG) signals. The key generator comprises two independent stages, namely, enrollment and verification-generation. In the latter, an algorithm for determining the keys is also proposed. 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 keys are released to different individuals. The performance of the proposed key generator is assessed using ECG signals from MIT-BIH database. Simulation results show a false accept rate (FAR) of 22.3% and a false reject rate (FRR) of 18.1%. The 128-bit key released by the generator proposed in this work can be used in several encryption algorithms.","PeriodicalId":254577,"journal":{"name":"2009 52nd IEEE International Midwest Symposium on Circuits and Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 52nd IEEE International Midwest Symposium on Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MWSCAS.2009.5236010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
In this paper, we present a wavelet-based 128-bit key generator using electrocardiogram (ECG) signals. The key generator comprises two independent stages, namely, enrollment and verification-generation. In the latter, an algorithm for determining the keys is also proposed. 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 keys are released to different individuals. The performance of the proposed key generator is assessed using ECG signals from MIT-BIH database. Simulation results show a false accept rate (FAR) of 22.3% and a false reject rate (FRR) of 18.1%. The 128-bit key released by the generator proposed in this work can be used in several encryption algorithms.