Towards the Integration of Reliability and Security Mechanisms to Enhance the Fault Resilience of Neural Networks

Nowadays, many electronic systems store valuable Intellectual Property (IP) information inside Non-Volatile Memories (NVMs). Designers widely use encryption mechanisms to enhance the integrity of such IPs and protect them from any unauthorized access or modification. At the same time, often such IPs...

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Autores principales:	Nikolaos Ioannis Deligiannis, Riccardo Cantoro, Matteo Sonza Reorda, Marcello Traiola, Emanuele Valea
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Artificial neural networks convolutional neural networks encryption fault detection fault injection non-volatile memories Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/ce17281b886a4d419a89839ecce4c9ba
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Towards the Integration of Reliability and Security Mechanisms to Enhance the Fault Resilience of Neural Networks

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