Secret-Key Agreement by Asynchronous EEG over Authenticated Public Channels

In this paper, we propose a new system for a sequential secret key agreement based on 6 performance metrics derived from asynchronously recorded EEG signals using an EMOTIV EPOC+ wireless EEG headset. Based on an extensive experiment in which 76 participants were engaged in one chosen mental task, t...

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Detalles Bibliográficos
Autores principales: Galis, Meiran, Milosavljević, Milan, Jevremović, Aleksandar, Banjac, Zoran, Makarov, Aleksej, Radomirović, Jelica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534527/
https://www.ncbi.nlm.nih.gov/pubmed/34682051
http://dx.doi.org/10.3390/e23101327
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author Galis, Meiran
Milosavljević, Milan
Jevremović, Aleksandar
Banjac, Zoran
Makarov, Aleksej
Radomirović, Jelica
author_facet Galis, Meiran
Milosavljević, Milan
Jevremović, Aleksandar
Banjac, Zoran
Makarov, Aleksej
Radomirović, Jelica
author_sort Galis, Meiran
collection PubMed
description In this paper, we propose a new system for a sequential secret key agreement based on 6 performance metrics derived from asynchronously recorded EEG signals using an EMOTIV EPOC+ wireless EEG headset. Based on an extensive experiment in which 76 participants were engaged in one chosen mental task, the system was optimized and rigorously evaluated. The system was shown to reach a key agreement rate of 100%, a key extraction rate of 9%, with a leakage rate of 0.0003, and a mean block entropy per key bit of 0.9994. All generated keys passed the NIST randomness test. The system performance was almost independent of the EEG signals available to the eavesdropper who had full access to the public channel.
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spelling pubmed-85345272021-10-23 Secret-Key Agreement by Asynchronous EEG over Authenticated Public Channels Galis, Meiran Milosavljević, Milan Jevremović, Aleksandar Banjac, Zoran Makarov, Aleksej Radomirović, Jelica Entropy (Basel) Article In this paper, we propose a new system for a sequential secret key agreement based on 6 performance metrics derived from asynchronously recorded EEG signals using an EMOTIV EPOC+ wireless EEG headset. Based on an extensive experiment in which 76 participants were engaged in one chosen mental task, the system was optimized and rigorously evaluated. The system was shown to reach a key agreement rate of 100%, a key extraction rate of 9%, with a leakage rate of 0.0003, and a mean block entropy per key bit of 0.9994. All generated keys passed the NIST randomness test. The system performance was almost independent of the EEG signals available to the eavesdropper who had full access to the public channel. MDPI 2021-10-11 /pmc/articles/PMC8534527/ /pubmed/34682051 http://dx.doi.org/10.3390/e23101327 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Galis, Meiran
Milosavljević, Milan
Jevremović, Aleksandar
Banjac, Zoran
Makarov, Aleksej
Radomirović, Jelica
Secret-Key Agreement by Asynchronous EEG over Authenticated Public Channels
title Secret-Key Agreement by Asynchronous EEG over Authenticated Public Channels
title_full Secret-Key Agreement by Asynchronous EEG over Authenticated Public Channels
title_fullStr Secret-Key Agreement by Asynchronous EEG over Authenticated Public Channels
title_full_unstemmed Secret-Key Agreement by Asynchronous EEG over Authenticated Public Channels
title_short Secret-Key Agreement by Asynchronous EEG over Authenticated Public Channels
title_sort secret-key agreement by asynchronous eeg over authenticated public channels
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534527/
https://www.ncbi.nlm.nih.gov/pubmed/34682051
http://dx.doi.org/10.3390/e23101327
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