Investigating The Impact Of Epilepsy On EEG-based Cryptographic Key Generation Systems | Zendy

Dang Tuan Nguyen | Zendy; Dat Tran | Zendy; Dharmendra Sharma | Zendy; Wanli Ma | Zendy

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Investigating The Impact Of Epilepsy On EEG-based Cryptographic Key Generation Systems

Author(s) -

Dang Tuan Nguyen,

Dat Tran,

Dharmendra Sharma,

Wanli Ma

Publication year - 2017

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2017.08.015

Subject(s) - computer science , electroencephalography , epilepsy , key generation , key (lock) , quantization (signal processing) , parametric statistics , artificial intelligence , cryptography , feature (linguistics) , speech recognition , pattern recognition (psychology) , algorithm , computer security , neuroscience , statistics , psychology , linguistics , philosophy , mathematics

In this study, we investigate the impact of epilepsy on EEG-based cryptographic key generation systems. Epilepsy is one of the brain disorders that involves in the EEG signal and hence it may have impact on the system. However, this issue has not been investigated. To solve this problem, we propose a system for cryptographic key generation from EEG signals, and experiment it with the Australian EEG dataset. We used parametric spectrum estimate technique for feature exaction, and devised an error-correction quantization technique that is useful for a noisy data such as EEG. We performed experiments on two groups of subjects, epileptic and non-epileptic to investigate the impact of epilepsy on the success rate of the system. Experimental results show that epilepsy actually has an impact on the performance of the system.

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