DocumentCode :
729536
Title :
Web-based multimodal biometric authentication application
Author :
Al-Hudhud, Ghada ; Alarfag, Eman ; Alkahtani, Shahad ; Alaskar, Afnan ; Almashari, Basmah ; Almashari, Hanna
Author_Institution :
Dept. of Inf. Technol., Coll. of Comput. & Inf. Sci. King Saud Univ., Riyadh, Saudi Arabia
fYear :
2015
fDate :
17-19 Feb. 2015
Firstpage :
1
Lastpage :
6
Abstract :
Biometric authentication systems are currently highly demanded, yet they are facing efficiency and accessibility challenges in terms of te unimodality. This paper addresses those problems and proposes a multimodal biometric system as a solution. The system includes two biometric models: Electroencephalography (EEG) and face recognition. In addition, the proposed multimodal biometric system includes a non-biometric model, known as SMS token. The work presented in this paper describes the feature extraction from the cloud storage of the biometric data and the best multimodal fusion technique for model combination.
Keywords :
biometrics (access control); cloud computing; electroencephalography; face recognition; feature extraction; message authentication; storage management; EEG; SMS token; Web-based multimodal biometric authentication application; biometric data; biometric models; cloud storage; electroencephalography; face recognition; feature extraction; multimodal biometric authentication systems; multimodal fusion technique; nonbiometric model; unimodality; Authentication; Brain models; Electroencephalography; Face; Face recognition; Feature extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology: Towards New Smart World (NSITNSW), 2015 5th National Symposium on
Conference_Location :
Riyadh
Print_ISBN :
978-1-4799-7625-6
Type :
conf
DOI :
10.1109/NSITNSW.2015.7176422
Filename :
7176422
Link To Document :
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