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Replay attacks and countermeasures against them

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dc.contributor.author BUJOR, Alexandru
dc.contributor.author BOZADJI, Artiom
dc.contributor.author GURSCHI, Gheorghe
dc.date.accessioned 2024-10-16T07:36:05Z
dc.date.available 2024-10-16T07:36:05Z
dc.date.issued 2024
dc.identifier.citation BUJOR, Alexandru; Artiom BOZADJI and Gheorghe GURSCHI. Replay attacks and countermeasures against them. In: Conferinţa tehnico-ştiinţifică a studenţilor, masteranzilor şi doctoranzilor = Technical Scientific Conference of Undergraduate, Master and PhD Students, Universitatea Tehnică a Moldovei, 27-29 martie 2024. Chișinău, 2024, vol. 2, pp. 793-796. ISBN 978-9975-64-458-7, ISBN 978 9975-64-460-0 (Vol.2). en_US
dc.identifier.isbn 978-9975-64-458-7
dc.identifier.isbn 978 9975-64-460-0
dc.identifier.uri http://repository.utm.md/handle/5014/28081
dc.description.abstract Voice authentication technology uses an individual's unique voice characteristics for secure identity verification, providing a seamless method to access devices and services. However, it faces challenges in maintaining robustness against security breaches and impersonation attempts. This study examines the effectiveness of voice authentication technology, focusing on its ability to analyze and differentiate between complex voice attributes like pitch, tone, and speech patterns. The study found that advanced voice authentication systems have high accuracy in recognizing and validating users based on voice biometrics, enhancing security for various applications. The findings emphasize the importance of continuous advancements voice authentication technology to counteract evolving security threats and ensure a safer and more reliable user experience across various sectors, including virtual assistants and customer service interfaces. en_US
dc.language.iso en en_US
dc.publisher Universitatea Tehnică a Moldovei en_US
dc.relation.ispartofseries Conferinţa tehnico-ştiinţifică a studenţilor, masteranzilor şi doctoranzilor = Technical Scientific Conference of Undergraduate, Master and PhD Students: Chişinău, 27-29 martie 2024. Vol. 2;
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject convolutional neural networks en_US
dc.subject attack en_US
dc.subject safe access en_US
dc.subject security en_US
dc.subject voice authentication en_US
dc.title Replay attacks and countermeasures against them en_US
dc.type Article en_US


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