A Novel FeFET Array-Based PUF: Co-optimization of Entropy Source and CRP Generation for Enhanced Robustness in IoT Security
Hanyong Shao, Yuejia Zhou, Weiqin Huang, Chang Su, Zhiyuan Fu, Wenpu Luo, Kechao Tang, Ru Huang · 2023
Enhancing the resistance of Physical Unclonable Function (PUF) to machine learning (ML) attacks while ensuring its reliability remains a critical challenge. In this work, we propose a novel strong PUF based on a 10×10 FeFET array, delivering high security, reliability, and reconfigurability. For the first time, the entropy source and CRP generation of PUF are co-optimized for robustness. We utilize the high variation in ferroelectric (FE) minor loop and high uniformity in major loop as reconfigurable static entropy source, then adopt non-linear Hamming distance comparison and window comparator for the generation of CPR. As a result, our approach reduces the accuracy of ML attacks by 20% compared to RRAM PUF, while keeping the raw bit error rate (BER) down to 1.7% at 100°C. Due to the high endurance of FeFETs, the capacity of reconfigurability reaches 1 × 108. The PUF fits well for security applications due to its robustness and energy-efficiency.