发表机构
School of Information Systems Engineering, Information Engineering University（信息工程大学信息系统工程学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对跨接收机场景下开集RFFI决策脆弱问题，提出由DSA和ROA组成的结构优先适配框架CRODA-ST，在WiSig ManyTx数据集上取得优异开集识别性能。
AI 中文摘要
射频指纹识别（RFFI）可为物联网设备提供物理层凭证，但当源接收机上校准的阈值迁移至目标接收机时，开集决策会变得脆弱。接收机偏移会降低已知发射机的置信度并引发误拒；闭集对齐则会产生相反效果，将未见的目标发射机拉入已知区域，提升误受率。本文提出CRODA-ST，一种面向单源单目标跨接收机开集RFFI的结构优先适配框架。其两个组件针对源校准拒判不可靠背后的瓶颈：判别性结构锚定（DSA）从有限的带标注目标注册样本中恢复目标接收机的已知类参考，面向拒判的对齐（ROA）降低锚定结构周边的接收机敏感置信度波动。在WiSig ManyTx数据集上，CRODA-ST达到0.9092的已知类准确率、0.9692的AUROC以及0.9580的OSCR。分数扫描分析进一步将FPR90降至0.0469。
英文摘要
Radio frequency fingerprint identification (RFFI) provides a critical physical-layer security mechanism for dynamic Internet of Things (IoT) and ad hoc networks. However, the decentralized and open nature of these networks imposes two strict deployment criteria: the credential must transfer reliably across physically dispersed, heterogeneous receivers, and it must decisively reject unregistered rogue traffic. Cross-receiver hardware shifts depress the confidence of registered devices and may also place unseen rogue transmitters in high-confidence known regions under naive domain adaptation, increasing false acceptance. To address these risks, we propose CRODA-ST, a joint optimization framework that couples Discriminative Structure Anchoring (DSA) with Rejection Oriented Alignment (ROA). Within this coupled objective, DSA establishes a stable target-known semantic foundation for shifted registered devices, while ROA regularizes the open-set decision boundaries governing rejection of unseen rogue transmitters. In the canonical WiSig setting, CRODA-ST achieves an open-set classification rate (OSCR) of 0.9580 and a target-domain false positive rate of 0.0469 at a 90% true positive rate (FPR90). A controllable LoRa simulation provides a complementary diagnostic under synthesized hardware distortions. At the distinct source-calibrated deployment operating point with rho = 0.80, CRODA-ST yields a target-unknown false acceptance rate (FAR) of 0.0075 in the evaluated setting.
