Static Random Access Memory (SRAM) Physically Unclonable Functions (PUFs) make use of intrinsic manufacturing variations in memory cells to derive device-unique responses. Employing such hardware-rooted fingerprints for authentication, this work demonstrates a threshold-based authentication proof of concept for constrained Industrial Internet of Things (IIoT) devices. The proposed scheme can reliably cap the the post-authentication bit error rate (BER) below 1 %. Inherent SRAM PUF unreliability is addressed by a resource-efficient combination of Hamming code (HC) Error Correction (EC) and Temporal Majority Voting (TMV). Increasing HC redundancy or TMV count significantly reduces the BER, albeit with diminishing returns and increasingly prohibitive computational overhead. Furthermore, this work quantifies the threshold gap between strict reliability and security constraints. This gap is reframed as a design budget which enables the resource-aware calibration of the acceptance threshold, PUF response length, and stabilization technique, without violating designed-for error limits. Larger responses make reliability optimizations increasingly obsolete. This comparative analysis establishes a comprehensive design space for PUF EC, guiding future implementations in balancing EC quality against resource constraints such as computational demand, power consumption, and implementation complexity.

翻译：静态随机存取存储器物理不可克隆函数利用存储单元固有的制造变异来生成设备特有的响应。本研究采用此类硬件根植的指纹进行认证，展示了面向受限工业物联网设备的基于阈值的认证概念验证。所提出的方案能够可靠地将认证后比特错误率控制在1%以下。通过汉明码纠错与时间多数投票的资源高效组合，解决了SRAM PUF固有的不可靠性问题。增加HC冗余或TMV计数可显著降低BER，但会面临边际效益递减以及计算开销急剧增加的问题。此外，本研究量化了严格可靠性约束与安全约束之间的阈值间隙。该间隙被重新定义为设计裕度，使得在不违反设计误差限制的前提下，能够根据资源感知需求校准接受阈值、PUF响应长度及稳定化技术。较长的响应使得可靠性优化的必要性逐渐降低。本对比分析建立了PUF纠错的综合设计空间，为在纠错质量与计算需求、功耗、实现复杂度等资源约束之间寻求平衡的未来实现提供指导。