基于非正交离散变换的物理不可克隆函数可靠性提升算法

Reliability enhancement algorithm for physical unclonable function based on non-orthogonal discrete transform

为了解决物理不可克隆函数(PUF)受外部环境和自身老化因素影响存在响应不稳定的问题,提出基于非正交离散(NOD)变换的PUF可靠性提升算法。首先,设计了一种重排序混淆器,将随机种子向量及PUF响应经重排序混淆器迭代处理后得到非正交混淆矩阵与混淆响应矩阵的内积,据此建立NOD谱,有效缓解了因PUF本身均匀性不足而产生偏向性密钥的问题;随后,通过分区编解码策略,赋予NOD谱一定的波动容错能力,将不稳定响应的影响限制在有限的范围,从而显著提高最终响应的可靠性。所提算法相较于传统基于纠错码的方法,需要的帮助数据更少。基于SRAM-XMC数据集进行实验,所提算法在对2949120组64位响应进行101次重复实验过程中平均可靠性达到99.97%,唯一性达到49.92%,均匀性达到50.61%。实验结果表明,所提算法能够在保证PUF响应均匀性与唯一性的同时有效提高可靠性。

A reliability enhancement algorithm for Physical Unclonable Function(PUF)was proposed to address the instability of PUF’s response caused by external and internal factors.The proposed algorithm is based on the Non-Orthogonal Discrete(NOD)transform.Firstly,a reorder mixer was designed to iteratively process the random seed vector and PUF response,resulting in the inner product of the non-orthogonal confusion matrix and the response confusion matrix,upon which the NOD spectrum was established.The algorithm effectively solved the bias of key caused by insufficient uniformity of PUF.Then,the partition encoding and decoding strategy enabled the NOD spectrum to have the ability to tolerate certain errors,significantly improving the reliability of the final response by limiting the impact of unstable responses to a limited range.Compared to traditional error correcting code-based methods,the proposed algorithm requires fewer auxiliary data.Experimental results on SRAM-XMC dataset show that,during 101 repeated experiments with 2949120 sets of 64-bit responses,the average reliability of the proposed algorithm reaches 99.97%,the uniqueness achieves 49.92%,and the uniformity reaches 50.61%.The experimental results demonstrate that the proposed algorithm can effectively improve reliability while ensuring uniformity and uniqueness of PUF responses.