Investigating the Impact of Epilepsy on EEG-based Cryptographic Key Generation Systems

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2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProcedia Computer Science
Subtitle of host publicationInternational Conference on Knowledge Based and Intelligent Information and ENgineering Systems (KES 2017)
Place of PublicationNetherlands
PublisherElsevier
Pages177-185
Number of pages9
Volume112
Edition2017
DOIs
Publication statusPublished - 1 Sep 2017
Event21st International Conference on Knowledge - Based and Intelligent Information and Engineering Systems - Marseille, France
Duration: 6 Sep 20178 Sep 2017

Publication series

NameProcedia Computer Science
PublisherElsevier BV
ISSN (Print)1877-0509

Conference

Conference21st International Conference on Knowledge - Based and Intelligent Information and Engineering Systems
Abbreviated titleKES 2017
CountryFrance
CityMarseille
Period6/09/178/09/17

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Nguyen, D., Tran, D., Sharma, D., & Ma, W. (2017). Investigating the Impact of Epilepsy on EEG-based Cryptographic Key Generation Systems. In Procedia Computer Science: International Conference on Knowledge Based and Intelligent Information and ENgineering Systems (KES 2017) (2017 ed., Vol. 112, pp. 177-185). (Procedia Computer Science). Netherlands: Elsevier. https://doi.org/10.1016/j.procs.2017.08.015