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Title: | A Review on Development of an EEG-based Biometric Authentication System |
Authors: | Ong, Zhi Ying Saidatul Ardeenawatie, Awang Vijean, Vikneswaran jean-624@hotmail.com |
Keywords: | Authentication Biometric EEG Processing Recognition |
Issue Date: | 2018 |
Publisher: | Universiti Malaysia Perlis (UniMAP) |
Citation: | Journal of Engineering Research and Education, vol.10, 2018, pages 39-48 |
Abstract: | The authentication system is the system that provides security and ensures confidentiality of information. Biometric systems provide the best security among other authentication systems. There are some classical approaches of biometric systems for authentication such as fingerprints, eyeballs and voices. However, the threat of fake fingerprints, eyeballs and recorded voices still compromise security walls. Electroencephalogram (EEG) signal is the electrical activity of the brain which may contain much useful information. It can possibly be used for building a robust biometric recognition because of its uniqueness. EEG signal is required to undergo advanced signal processing in order to get the useful information. There are three main stages included in advanced signal processing namely pre-processing, feature extraction and classification. The techniques of signal processing are categorized into two groups which are linear and non-linear. Although many different research activities have been reported, however, a systematic exploration of research findings yet to be done. Therefore, this paper aims to critically review significant findings in the field of signal processing and present the analysis in a simplistic manner for readers under findings. |
Description: | Link to publisher's homepage at http://jere.unimap.edu.my |
URI: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/57944 |
ISSN: | 2232-1098 |
Appears in Collections: | Journal of Engineering Research and Education (JERE) |
Files in This Item:
File | Description | Size | Format | |
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A Review on Development of an EEG-based Biometric Authentication.pdf | 751.22 kB | Adobe PDF | View/Open |
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