Normalization and Multi-Valued Symbol Extraction From RO-PUFs for Enhanced Uniform Probability Distributions

Physical Unclonable Functions (PUFs) offer the possibility for on-chip generation of unique fingerprints for integrated circuits. Ring-oscillator (RO) PUFs are small and easy to configure on Field Programmable Gate Arrays (FPGAs) and thus received great attention over the years. In the state-of-the-art two neighboring ROs are compared and mapped to only a single bit of information. Few publications aims to extract more bits out of one PUF-cell, but struggle with non-uniform distributions. In this brief multi-valued symbol extraction is presented as a method to extract more bits of information out of each individual RO. A new post-processing approach is introduced to produce close-to-ideal uniformly distributed responses independent of the underlying physically probability distribution. To eliminate bias, caused by placement inequalities, multiple methods of normalization are utilized and analyzed by means of area and complexity. Based on metrics for symbol transmission, the Euclidean-distance and entropy are used as metrics to evaluate the uniqueness and reliability of multi-valued PUFs. This new approach allows to increase the amount of extracted information to 3 bits per RO.