Unreliable XOR Arbiter PUFs were broken by a machine learning attack, which targets the underlying Arbiter PUFs individually. However, reliability information from the PUF was required for this attack. We show that, for the first time, a perfectly reliable XOR Arbiter PUF, where no reliability information is accessible, can be efficiently attacked in the same divide-and-conquer manner. Our key insight is that the responses of correlated challenges also reveal their distance to the decision boundary. This leads to a chosen challenge attack on XOR Arbiter PUFs. The effectiveness of our attack is confirmed through PUF simulation and FPGA implementation.

翻译：不可靠的XOR仲裁器PUF曾通过机器学习攻击被破解，该攻击针对底层仲裁器PUF逐个击破。然而，该攻击需要获取PUF的可靠性信息。我们首次证明：当无法获取任何可靠性信息时，完全可靠的XOR仲裁器PUF同样能通过分治策略被高效攻击。关键洞察在于，相关性挑战的响应也会揭示其与决策边界的距离，由此衍生出针对XOR仲裁器PUF的选择性挑战攻击。通过PUF仿真与FPGA实现验证了该攻击的有效性。