A key requirement for most security solutions is to provide secure cryptographic key storage in a way that will easily scale in the age of the Internet of Things. In this paper, we focus on providing such a solution based on Physical Unclonable Functions (PUFs). To this end, we focus on microelectromechanical systems (MEMS)-based gyroscopes and show via wafer-level measurements and simulations, that it is feasible to use the physical and electrical properties of these sensors for cryptographic key generation. After identifying the most promising features, we propose a novel quantization scheme to extract bit strings from the MEMS analog measurements. We provide upper and lower bounds for the minimum entropy of the derived bit strings and fully analyze the intra- and inter-class distributions across the operation range of the MEMS device. We complement these measurements via Monte-Carlo simulations based on the distributions of the parameters measured on actual devices. We also propose and evaluate a complete cryptographic key generation chain based on fuzzy extractors. We derive a full entropy 128-bit key using the obtained min-entropy estimates, requiring 1219 bits of helper data with an (authentication) failure probability of 4 . 10 -7 . In addition, we propose a dedicated MEMS-PUF design, which is superior to our measured sensor, in terms of chip area, quality and quantity of key seed features.
['Oliver Willers', 'Christopher Huth', 'Jorge Guajardo', 'Helmut Seidel']
MEMS Gyroscopes as Physical Unclonable Functions