文章基本信息

标题：CENTRAL INTELLIGENT BIOMETRIC AUTHENTICATION BASED ON VOICE RECOGNITION AND FUZZY LOGIC
本地全文：下载
作者：ALIA KARIM ABDUL-HASSAN ; IMAN HASSOON HADI
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：16
页码：4412-4423
出版社：Journal of Theoretical and Applied
摘要：Reliable identity management must be built with an accurate user identity recognition method. This recognition usually is the core of the authentication method which is the essential part of any identity management system. The authentication must carefully be designed, especially when it is used among different service providers. The authentication is a user identity verifying and protecting mechanism. It consists of three main components, user identity attributes, the verification method, and the log-in mechanism. The log-in component has great impact on authentication, when the user needs to be authenticated to be given access to several service providers. In addition, the verification of the claimed user attributes, involve the decisive role in the authentication because it will produce the final decision of the identity proving process, so it is important to be accurate and intelligent as much as possible. In this paper, a central intelligent biometric authentication approach is proposed; this authentication is based on the Mel-frequency Cepstral coefficients (MFCC) voice attributes, fuzzy classifier, and client-server model as log-in mechanism. The proposed fuzzy classifier depends on the fuzzy set inner product and a predefined threshold. This classifier is designed as an intelligent identity verification method. The experiments show 95.45% accuracy in offline user authentication using ELSDSR dataset.
关键词：Central Authentication; Voice; Fuzzy Logic; MFCC