International Journal of Advanced Networking and Applications

Amer A. Sallam ¹, Amin Saif ², Mogeeb A. Saeed ¹, Siham A. Mohammed ³

Affiliations
1 Department of Computer Networks & Distributed Systems, Taiz University, Taiz, YE
2 Department of Mechatronics Engineering & Robotics, Taiz University, Taiz, YE
3 Department of Information Technology, Faculty of Engineering & IT, Taiz University, Taiz, YE

Abstract

Authentication with textual password has several limitations: passwords have low entropy in practice, are often difficult to remember, are vulnerable "shoulder surfing". Biometric system does not meet requirement as well. It relies upon unchanging features that have a lifetime as long as the individual. To avoid this limitation, we start to authenticate with thinking pass thought. User performs one mental task such as thinking of a word or phrase. In this study, Electroencephalography (EEG) was used as method for monitoring andrecording the electrical activity of the brain. These signals can be captured and processed to get the useful information that can be used in pas-thoughts authentication system. Suitable analysis is essential for EEG to differentiate between best and worst tasks used for authentication. This study focuses on usefulness of EEG signal to identify best tasks suitable for the pass-thoughts authentication system. Artificial neural network (ANN) is used to train the data set. Then tests are conducted on the testing data of EEG signal to identify best and worst tasks suitable for authentication. Finally, the system performance was evaluated by computing the accuracy and thereforepromising results were obtained.

Keywords

Electroencephalography, Artificial Neural Network, Discrete Wavelet Transform.

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