A Study on the Impact of Alcoholism on EEG-based Cryptographic Key Generation Systems

D Sharma, Dat Tran, Dang Nguyen

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

Abstract

Alcoholism is one of the brain disorders that involves in electroencephalogram (EEG) signals and have impact on EEG-based systems. However, this issue has not been investigated. In this paper, we propose an EEG-based cryptographic key generation system using EEG signals and present experiments performed on two groups of subjects, alcoholic and non-alcoholic groups in the Alcoholism database. This EEG-based cryptographic key generation system is based on an assumption that EEG signal is quasi-stationary if the time window is sufficiently short. With this assumption, stable EEG features are extracted to generate cryptographic keys. The impact of alcoholism on performance of the system is analysed based on our experimental results.

Original languageEnglish
Title of host publication2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
EditorsHussein Abbass, Carlos A. Coello Coello, Hemant Kumar Singh
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages79-85
Number of pages7
ISBN (Electronic)9781728125473
ISBN (Print)9781728125480
DOIs
Publication statusPublished - 1 Dec 2020
Event2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 - Virtual, Canberra, Australia
Duration: 1 Dec 20204 Dec 2020

Publication series

Name2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

Conference

Conference2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
CountryAustralia
CityVirtual, Canberra
Period1/12/204/12/20

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