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Novel 'unclonable' tag may help combat counterfeiters 

Discovering that your new designer handbag or gold watch is a fake is costly and annoying, and counterfeit medical devices or drugs could have even more serious consequences, researchers said.

Published: 07th February 2019 05:53 PM  |   Last Updated: 07th February 2019 05:53 PM   |  A+A-

counterfeit insurance documents

Image for representational purpose only.

By PTI

LONDON: Scientists have created an "unclonable" tag that is based on random patterns that can not be replicated even by the manufacturer, an advance that could help prevent identify counterfeit products.

Discovering that your new designer handbag or gold watch is a fake is costly and annoying, and counterfeit medical devices or drugs could have even more serious consequences, researchers said.

However, seemingly as soon as manufacturers develop a new method to ensure product authenticity, counterfeiters find a way to outsmart it.

Researchers from the University of Copenhagen in Denmark have created an "unclonable" tag that can never be replicated, even by the manufacturer.

Each year, counterfeit goods cost billions of dollars in economic losses.

These knock-offs, typically of inferior quality, often masquerade as luxury brands.

Manufacturers have tried to incorporate unique tags or barcodes on their products so that store owners and consumers can verify a product's authenticity, but counterfeiters often figure out how to copy these.

The researchers developed an authentication system using physically unclonable functions (PUFs) -- tags based on random processes that are impossible to replicate.

As they explain in the study published in the journal ACS Applied Materials & Interfaces, an example of a PUF would be throwing a handful of sand on a surface.

Each throw generates a random pattern that cannot be copied.

To develop their anti-counterfeiting system, the researchers laser-printed QR codes on paper and then sprayed the PUF pattern on the surface.

The PUF inks contained microparticles, which formed random patterns that showed up as white spots on a black background when magnified.

To validate their system, the team generated 10,000 tags and imaged them with a smartphone camera to establish a registry.

Then, they re-imaged the tags with different smartphone readers and tried to match them to the registry.

The system correctly identified 76 per cent of the PUF tags.

None of the tags were identified incorrectly, but some codes that were dirty or out-of-focus required an additional scan.

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