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

By Tommaso Addabbo, Ada Fort, Mauro DI MARCO, Luca Pancioni and Valerio Vignoli


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

Publisher: 'Institute of Electrical and Electronics Engineers (IEEE)'
Year: 2013
DOI identifier: 10.1109/ISCAS.2013.6572393
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