{"title":"脉冲主动均值(PAM):一种支持双重安全认证的PIN特征提取算法","authors":"S. Safie, J. Soraghan, L. Petropoulakis","doi":"10.1109/ISIAS.2011.6122821","DOIUrl":null,"url":null,"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","PeriodicalId":139268,"journal":{"name":"2011 7th International Conference on Information Assurance and Security (IAS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Pulse Active Mean (PAM): A PIN supporting feature extraction algorithm for doubly secure authentication\",\"authors\":\"S. Safie, J. Soraghan, L. Petropoulakis\",\"doi\":\"10.1109/ISIAS.2011.6122821\",\"DOIUrl\":null,\"url\":null,\"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\",\"PeriodicalId\":139268,\"journal\":{\"name\":\"2011 7th International Conference on Information Assurance and Security (IAS)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 7th International Conference on Information Assurance and Security (IAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIAS.2011.6122821\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 7th International Conference on Information Assurance and Security (IAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIAS.2011.6122821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pulse Active Mean (PAM): A PIN supporting feature extraction algorithm for doubly secure authentication
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