Diffie-Hellman Protocol with a Combination of Hyperelliptic Curves and Neural Synchronization
ABSTRACT: This work proposes a new cryptosystem, combining a Diffie-Hellman protocol in which hyperelliptic curves over GF(2n) are implemented, with a Tree Parity Machine (TPM) synchronization. Security proposed for this cryptosystem is focused on overcoming a weakness of neuronal synchronization. S...
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Universidad de Tarapacá.
2018
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oai:scielo:S0718-330520180005000062018-12-10Diffie-Hellman Protocol with a Combination of Hyperelliptic Curves and Neural SynchronizationAraya Villanueva,AngeloJiron Araya,IvanSoto Gomez,Ismael Cryptography Hyperelliptic Curves Neural Synchronization ABSTRACT: This work proposes a new cryptosystem, combining a Diffie-Hellman protocol in which hyperelliptic curves over GF(2n) are implemented, with a Tree Parity Machine (TPM) synchronization. Security proposed for this cryptosystem is focused on overcoming a weakness of neuronal synchronization. Specifically, the stimulus vector that is public, which allows an attacker to try to synchronize with one of the participants of the synchronization. Focusing on this weakness, there are the following attacks: genetic attack, geometric attack and probabilistic attack. In the proposed cryptosystem, the initial stimulus vector will be hidden, because this vector is obtained as the common secret key in the Diffie-Hellman protocol. Then in each iteration, the stimulus vectors will be kept secret. This condition causes the learning time tlear to increase by a term of approximately 115% regarding the synchronization time tsync on average when the proposed cryptosystem is compared to the classic TPM synchronization.info:eu-repo/semantics/openAccessUniversidad de Tarapacá.Ingeniare. Revista chilena de ingeniería v.26 suppl.1 20182018-11-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-33052018000500006en10.4067/S0718-33052018000500006 |
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Scielo Chile |
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Scielo Chile |
language |
English |
topic |
Cryptography Hyperelliptic Curves Neural Synchronization |
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Cryptography Hyperelliptic Curves Neural Synchronization Araya Villanueva,Angelo Jiron Araya,Ivan Soto Gomez,Ismael Diffie-Hellman Protocol with a Combination of Hyperelliptic Curves and Neural Synchronization |
description |
ABSTRACT: This work proposes a new cryptosystem, combining a Diffie-Hellman protocol in which hyperelliptic curves over GF(2n) are implemented, with a Tree Parity Machine (TPM) synchronization. Security proposed for this cryptosystem is focused on overcoming a weakness of neuronal synchronization. Specifically, the stimulus vector that is public, which allows an attacker to try to synchronize with one of the participants of the synchronization. Focusing on this weakness, there are the following attacks: genetic attack, geometric attack and probabilistic attack. In the proposed cryptosystem, the initial stimulus vector will be hidden, because this vector is obtained as the common secret key in the Diffie-Hellman protocol. Then in each iteration, the stimulus vectors will be kept secret. This condition causes the learning time tlear to increase by a term of approximately 115% regarding the synchronization time tsync on average when the proposed cryptosystem is compared to the classic TPM synchronization. |
author |
Araya Villanueva,Angelo Jiron Araya,Ivan Soto Gomez,Ismael |
author_facet |
Araya Villanueva,Angelo Jiron Araya,Ivan Soto Gomez,Ismael |
author_sort |
Araya Villanueva,Angelo |
title |
Diffie-Hellman Protocol with a Combination of Hyperelliptic Curves and Neural Synchronization |
title_short |
Diffie-Hellman Protocol with a Combination of Hyperelliptic Curves and Neural Synchronization |
title_full |
Diffie-Hellman Protocol with a Combination of Hyperelliptic Curves and Neural Synchronization |
title_fullStr |
Diffie-Hellman Protocol with a Combination of Hyperelliptic Curves and Neural Synchronization |
title_full_unstemmed |
Diffie-Hellman Protocol with a Combination of Hyperelliptic Curves and Neural Synchronization |
title_sort |
diffie-hellman protocol with a combination of hyperelliptic curves and neural synchronization |
publisher |
Universidad de Tarapacá. |
publishDate |
2018 |
url |
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-33052018000500006 |
work_keys_str_mv |
AT arayavillanuevaangelo diffiehellmanprotocolwithacombinationofhyperellipticcurvesandneuralsynchronization AT jironarayaivan diffiehellmanprotocolwithacombinationofhyperellipticcurvesandneuralsynchronization AT sotogomezismael diffiehellmanprotocolwithacombinationofhyperellipticcurvesandneuralsynchronization |
_version_ |
1714203463670300672 |