Efficient Attack on Non-linear Current Mirror PUF with Genetic Algorithm
Qingli Guo, Jing Ye, Yue Hong Gong, Yu Hu, Xiaowei Li · 2016
Physical Unclonable Function (PUF) is a new hardware security primitive that exploits the manufacturing variations of integrated circuits. Traditional arbiter PUF is vulnerable to machine learning based modeling attacks due to its linearity. Current mirror PUF uses non-linear current mirror to bring non-linearity into the challenge-response relationship and is claimed resistant to modeling attacks. This paper further tests its security, and proves that the current mirror PUF is not as secure as claimed. A genetic algorithm based method is proposed to attack the current mirror PUF. By modeling the relationship between the output current and the input current of each current mirror, and fitting the model using genetic algorithm, we are able to predict the responses of current mirror PUF. Experiments prove that the prediction accuracy towards current mirror PUF is up to 99.27%.