Pulse Active Mean (PAM): A PIN supporting feature extraction algorithm for doubly secure authentication

S. Safie, J. Soraghan, L. Petropoulakis
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引用次数: 6

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
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
本文提出了一种新的特征提取技术——脉冲有效均值(PAM),该技术应用于心电图的生物特征识别。提出了一种利用PAM算法的重要属性作为个人识别码(PIN)的双重安全心电认证框架。利用PIN提取不同位置的心电特征,生成唯一的特征向量。正确的PIN和心电信号的存在使所提出的认证框架具有双重安全性。通过对100名PTB (Physikalisch-Technische Bundesanstalt)受试者的受试者工作特征(ROC)曲线与传统的时间和幅度特征提取技术进行比较,评价了PAM的性能。研究了不同PIN值对生物识别性能的影响。本文表明,不同的PIN值在提供一致的认证性能的同时,会产生不同的特征向量集
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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