Murataj Irdi, Magosso Chiara, Carignano Stefano, Fretto Matteo, Ferrarese Lupi Federico, Milano Gianluca
Advanced Materials Metrology and Life Sciences Division, INRiM (Istituto Nazionale di Ricerca Metrologica), Turin, Italy.
Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy.
Nat Commun. 2024 Dec 11;15(1):10576. doi: 10.1038/s41467-024-54492-8.
Besides causing financial losses and damage to the brand's reputation, counterfeiting can threaten the health system and global security. In this context, physical unclonable functions (PUFs) have been proposed to overcome limitations of current anti-counterfeiting technologies. Here, we report on artificial fingerprints that can be directly engraved on a wide range of substrates through self-assembled block-copolymer templating as nanoscale PUFs for secure authentication and identification. Results show that morphological features can be exploited to encode fingerprint-like nanopatterns in binary code matrices representing a unique bit stream of information characterized by high uniqueness and entropy. A strategy based on computer vision concepts for authentication/identification in real-world scenarios is reported. Long-term reliable operation and robust authentication/identification against thermal treatment at cryogenic and high temperatures of the PUF have been demonstrated. These results pave the way for the realization of PUFs embracing the inherent stochasticity of self-assembled materials at the nanoscale.
除了造成经济损失和损害品牌声誉外,假冒伪劣还会威胁卫生系统和全球安全。在此背景下,有人提出使用物理不可克隆功能(PUF)来克服当前防伪技术的局限性。在此,我们报告了一种人工指纹,它可以通过自组装嵌段共聚物模板作为纳米级PUF直接刻在各种基材上,用于安全认证和识别。结果表明,形态特征可用于在二进制代码矩阵中编码类似指纹的纳米图案,该矩阵代表具有高独特性和熵的唯一信息流。报告了一种基于计算机视觉概念的在现实场景中进行认证/识别的策略。已经证明了PUF在低温和高温下经过热处理后的长期可靠运行以及强大的认证/识别能力。这些结果为实现包含纳米级自组装材料固有随机性的PUF铺平了道路。