Publication:

Development of hashing algorithm for PUF verifications

In this project we implement a Gabor Hash algorithm that suit with our type of tokens. We decided to implement a 2D Gabor function; study the algorithm and optimize its parameter (frequency and level of subsampling) so we can improve its performance. Once we have done this we have process 52 different tokens and analyze the results. We also explain how to generate our tokens, their characteristics and the way they work. Due to the results analyzed we have conceptualized a Cluster algorithm to identify bias in the manufacturing process which can influence in the randomness of the tokens. We study if the print process and the number of particles influence in the randomness of the tokens. We also try different ways of plotting the cluster in 3D and the way to represent the values. Finally we implement a Minimum Reference Distance algorithm to overcome those bias and explain how to do it.