A robust architecture of physical unclonable function based on Memristor crossbar array

During the past two decades, Physical Unclonable Functions (PUF) remained under discussion as strong hardware security primitives. As compared to conventional technology, memristor-based PUFs got tremendous attraction due to their simple and easy architecture, high endurance, low energy consumption, small size, and low cost. The inherent high variability of memristive devices makes it an ideal candidate for the generation of unique fingerprints for individual devices. By exploiting this variation, we propose a novel architecture dual memristive crossbar (DuMXbar) that integrates two memristive crossbar PUFs implemented with two different memristor devices. Each PUF generates highly uncorrelated response pairs. The simulation results of DuMXbar PUF prove that it is comparatively more robust against machine learning (ML) based classification algorithms like logistic regression and support vector machine. We have also proposed a secure authentication protocol for DuMXbar PUF to restrict the prediction accuracy of ML algorithms close down to 50% (ideal).