We propose to exploit a two-neurons Cellular Neural Network (CNN) to design a basic 1-bit Physically Unclonable Function (PUF). The analysis discussed in this work, derived from the general theory of CNNs, has been validated by experimental results.

Addabbo, T., Fort, A., DI MARCO, M., Pancioni, L., Vignoli, V. (2013). A 1-bit Physically Unclonable Function based on a two-neurons CNN. In Proceedings - IEEE International Symposium on Circuits and Systems (pp.2529-2532) [10.1109/ISCAS.2013.6572393].

A 1-bit Physically Unclonable Function based on a two-neurons CNN

ADDABBO, TOMMASO;FORT, ADA;DI MARCO, MAURO;PANCIONI, LUCA;VIGNOLI, VALERIO
2013-01-01

Abstract

We propose to exploit a two-neurons Cellular Neural Network (CNN) to design a basic 1-bit Physically Unclonable Function (PUF). The analysis discussed in this work, derived from the general theory of CNNs, has been validated by experimental results.
2013
9781467357609
Addabbo, T., Fort, A., DI MARCO, M., Pancioni, L., Vignoli, V. (2013). A 1-bit Physically Unclonable Function based on a two-neurons CNN. In Proceedings - IEEE International Symposium on Circuits and Systems (pp.2529-2532) [10.1109/ISCAS.2013.6572393].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/45779
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