On Reliability Hardening of FPGA based RO-PUF by using Regression Methodologies

Physical Unclonable Function (PUF) is a rapidly growing hardware security primitive. In reconfigurable systems, applications requiring high security generate the secret keys using PUFs. Due to the limited control over an FPGA fabric, it is challenging to design a PUF with 100% reliability. In this work, we propose a novel method of improving the reliability of an RO PUF under varying operating temperature. We first analyze the impact of temperature on the device characteristics that are responsible for variations in the RO frequency by using linear and non-linear regression methodologies. Later, we use this knowledge to correct the output response bit flips to improve reliability. Our proposed method is evaluated on a large dataset of 50 Xilinx 28nm Artix-7 XC7A35T FPGAs, each containing 6592 ROs at six different operating temperatures. Our experiments prove that we can correct the unreliable key back to a reliable one, thus achieving a higher reliability at different operating temperatures.