Polymer banknotes are the trend for printed currency and have been adopted by more than fifty countries worldwide. However, over the past years, the quantity of polymer counterfeits has been increasing, so has the quality of counterfeits. This shows that the initial advantage of bringing a new polymer technology to fight against counterfeiting is reducing. To maintain one step ahead of counterfeiters, we propose a novel anti-counterfeiting technique called Polymer Substrate Fingerprinting (PSF). Our technique is built based on the observation that the opacity coating, a critical step during the production of polymer notes, is a stochastic manufacturing process, leaving uneven thickness in the coating layer and the random dispersion of impurities from the ink. The imperfections in the coating layer result in random translucent patterns when a polymer banknote is back-lit by a light source. We show these patterns can be reliably captured by a commodity negative-film scanner and processed into a compact fingerprint to uniquely identify each banknote. Using an extensive dataset of 6,200 sample images collected from 340 UK banknotes, we show that our method can reliably authenticate banknotes, and is robust against rough daily handling of banknotes. Furthermore, we show the extracted fingerprints contain around 900 bits of entropy, which makes it extremely scalable to identify every polymer note circulated globally. As compared with previous or existing anti-counterfeiting mechanisms for banknotes, our method has a distinctive advantage: it ensures that even in the extreme case when counterfeiters have procured the same printing equipment and ink as used by a legitimate government, counterfeiting banknotes remains infeasible because of the difficulty to replicate a stochastic manufacturing process.
翻译:但是,过去几年来,聚合物假冒的数量一直在增加,而假冒的质量也随之下降。这显示,引进新的聚合物技术来打击假冒的最初优势正在减少。为了比假冒者更早一步,我们提议采用一种新型的反伪造技术,称为聚合体基底指纹印刷(PSF)。我们的技术基于以下观察而建立:不透明涂层是生产聚合物纸币过程中的一个关键步骤,它甚至是一个杂乱的制造过程,在涂层中留下不均匀的厚厚度,以及油墨中杂质的随机分散。涂层中的不完善之处导致随机的转基因模式,因为一个光源反射出聚合体钞票。我们展示这些模式可以可靠地被一个商品负色扫描器所捕捉,并被加工成一个可以独特地识别每个钞票的缩印点。我们用了一个从340张英国钞票中收集的6200个样本的庞大数据集。我们用的是纸钞票本,我们用这个方法来对每张纸质钞票进行精确的处理。我们用的是,我们用这个方法可以可靠地在纸上记录上显示,我们用来记录。