A 1-bit Physically Unclonable Function based on a two-neurons CNN
Tommaso Addabbo, Ada Fort, Mauro Di Marco, Luca Pancioni, Valerio Vignoli · 2013
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.