Volume & Issue no: Volume 3, Issue 4, July - August 2014
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Title: |
Artificial Immune System Approach for Access Control Based on EEG Signals |
Author Name: |
Wael H. Khalifa, Abdel Badeeh M. Salem and Mohamed I. Roushdy |
Abstract: |
Abstract: Access control is one of the main issues facing
companies and people; Whether it’s a physical location or
sensitive data, finding secure means to manage access control
is always a challenge. Electroencephalogram (EEG) is the
recording of electrical activity from the surface of the brain.
Researchers has showed that there is individuality in the EEG
signals, accordingly its can be used as a biometric for access
control. In this paper, we present an artificial immune system
inspired approach for access control using EEG signals. The
Physionet EEG Motor/Movement/ Imagery dataset is used to
validate this approach. The dataset consists of signals for over
a hundred users. The dataset is imported to EEG lab for the
preprocessing phase, then we use artificial immune system
based algorithm for user matching. The algorithm yielded to a
40% accuracy, we will discuss in the paper why that happened
and how to improve the accuracy.
Keywords: EEG, Access Control, Security, Artificial
Immune System. |
Cite this article: |
Wael H. Khalifa, Abdel Badeeh M. Salem and Mohamed I. Roushdy , "
Artificial Immune System Approach for Access Control Based on EEG Signals" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 3, Issue 4, July - August 2014 , pp.
001-005 , ISSN 2278-6856.
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