Breaking XOR Arbiter PUFs without Reliability Information

Authors: Niloufar Sayadi, Phuong Ha Nguyen, Marten van Dijk, Chenglu Jin
Published: 2023-12-03

Source: https://arxiv.org/abs/2312.01256

PDF: https://arxiv.org/pdf/2312.01256

AIにより推定されたラベル

PUFの評価手法 攻撃手法 ウォーターマーキング

※ こちらのラベルはAIによって自動的に追加されました。そのため、正確でないことがあります。
詳細は文献データベースについてをご覧ください。

Abstract

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.