Jung Uihoon, Beak Chang-Jae, Kim Kitae, Na Jun-Hee, Lee Sin-Hyung
School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 702-701, Republic of Korea.
School of Advanced Fusion Studies, Department of Intelligent Semiconductor Engineering, University of Seoul, 163 Seoulsiripdaero, Dongdaemun-gu, Seoul 02504, Republic of Korea.
ACS Nano. 2024 Oct 8;18(40):27642-27653. doi: 10.1021/acsnano.4c09080. Epub 2024 Sep 29.
The increasing menace of counterfeiting and information theft underscores the urgent need for security platforms compatible with both micro- and nanoelectronics. Existing methods for anticounterfeiting labeling and cryptographic systems rely on unclonable patterns derived from the unpredictable variability of physical phenomena. However, these approaches impose limitations on the scalability of security components. Here we present a scalable platform for photoresponsive physically unclonable functions based on oxide particle kinetics in polymer solutions. The stochastic agglomeration process occurring during the formation of polymer films with dispersed oxide particles yields random patterns, with pixel sizes scalable from micro to nanoscales. We produce mechanically flexible and self-destructible optical unclonable function patterns utilizing oxide aggregates on a polymer film. Moreover, we establish a strategy for generating electrical unclonable patterns on a conducting polymer film. This involves covering the polymer film with an aggregate pattern mask, which serves as an ultraviolet-blocking layer for randomly exposing the film to ultraviolet ozone treatment. These unclonable patterns constitute robust and compact security systems, exhibiting effective resilience against machine-learning attacks (∼50% prediction error for training data sets of 1000). The developed scalable platforms for physically unclonable functions provide a hardware solution for robust cryptographic applications.
假冒和信息盗窃的威胁日益增大,凸显了对兼容微电子和纳米电子的安全平台的迫切需求。现有的防伪标签和加密系统方法依赖于源自物理现象不可预测变异性的不可克隆图案。然而,这些方法对安全组件的可扩展性施加了限制。在此,我们基于聚合物溶液中的氧化物颗粒动力学,提出了一种用于光响应性物理不可克隆功能的可扩展平台。在含有分散氧化物颗粒的聚合物膜形成过程中发生的随机团聚过程产生随机图案,像素尺寸可从微米级扩展到纳米级。我们利用聚合物膜上的氧化物聚集体制作出机械柔性且可自毁的光学不可克隆功能图案。此外,我们制定了一种在导电聚合物膜上生成电不可克隆图案的策略。这包括用聚集体图案掩膜覆盖聚合物膜,该掩膜用作紫外线阻挡层,用于将膜随机暴露于紫外线臭氧处理。这些不可克隆图案构成了强大而紧凑的安全系统,对机器学习攻击表现出有效的抵御能力(对于1000个训练数据集,预测误差约为50%)。所开发的用于物理不可克隆功能的可扩展平台为强大的加密应用提供了一种硬件解决方案。