POSTER: Attack on Non-Linear Physical Unclonable Function

Jing Ye, Yu Hu, Xiaowei Li
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引用次数: 16

Abstract

Physical Unclonable Function (PUF) is a promising hardware security primitive with broad application prospect. However, the strong PUF with numerous Challenge and Response Pairs (CRPs), e.g. the arbiter PUF, is vulnerable to modeling attacks. There are two major kinds of countermeasures. One is restricting CRP access interface, such as controlled PUF and XOR arbiter PUF, which unfortunately has been broken with the help of side-channels. The other is using non-linear electronic characteristics to produce CRPs, such as the current mirror PUF and the voltage transfer PUF. They are only proved to be resistant to SVM based attack, while no more analysis is further explored so far. In this paper, we propose an attack method based on compound heuristic algorithms of evolution strategy, simulated annealing, and ant colony to efficiently attack these two non-linear PUFs. This paper reveals that current mirror and voltage transfer are still not able to help strong PUF resist attacks. Our experimental results show that the average CRP prediction accuracy is as high as 99%.
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海报:攻击非线性物理不可克隆函数
物理不可克隆函数(PUF)是一种很有前途的硬件安全原语,具有广阔的应用前景。然而,具有大量挑战和响应对(CRPs)的强PUF,例如仲裁者PUF,容易受到建模攻击。主要有两种对策。一是限制CRP访问接口,如受控PUF和XOR仲裁PUF,不幸的是,这些接口在侧信道的帮助下已经被打破。另一种是利用非线性电子特性产生crp,如电流镜PUF和电压转移PUF。它们只被证明能够抵抗基于支持向量机的攻击,目前还没有进一步的分析。本文提出了一种基于进化策略、模拟退火和蚁群的复合启发式算法的攻击方法来有效地攻击这两种非线性puf。本文揭示了电流镜像和电压转移仍然不能帮助强PUF抵抗攻击。我们的实验结果表明,平均CRP预测准确率高达99%。
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