Soft Response Generation and Thresholding Strategies for Linear and Feed-Forward MUX PUFs

In this work, we present probability based response generation schemes for MUX based Physical Unclonable Functions (PUFs). Compared to previous implementations where temporal majority voting (TMV) based on limited samples and coarse criteria was utilized to determine final responses, our design can collect soft responses with detailed probability information using simple on-chip circuits. Thresholds with fine accuracy are applied to efficiently distinguish stable and unstable challenge response pairs (CRPs). A 32nm test chip including both linear and feed-forward MUX PUFs was implemented for concept verification. Based on a detailed analysis of the hardware data, we propose several enhanced thresholding strategies for determining stable CRPs. For instance, a stringent threshold can be imposed in enrollment phase for selecting good CRPs, while a relaxed threshold can be used during normal authentication phase. Experimental data shows a high degree of uniqueness and randomness in the PUF responses which can be attributed to the carefully optimized circuit layout. Finally, output characteristic of a feed-forward MUX PUF was compared to that of a standard linear MUX PUF from the same 32nm chip.