Advanced Technologies to End Art Forgeries

Posted by Alexandra Rotunda on

Advanced Technologies to End Art Forgeries

             Imagine walking into an estate sale being told to expect an original Frida Kahlo.  It looks like a Frida Kahlo, the canvas appears to be from her era, and the painting has been kept in near perfect condition.  But, unbeknownst to the naked eye, this painting is a fake!  Questions we may ask ourselves are how can this be?  How are these fakes and forgeries not immediately identified?  It is because art frauds can be so exact and precise that it will fool even the most senior curator.  Welcome, all, to the twenty-first century where technology has significantly advanced to be able to perform the “behind the scenes” work to authenticate highly sought after and valuable artwork. 

Art Gallery

             The business of art fraud defines itself as the deliberate false representation of the artist, age, origins, or ownership of a work of art in order to reap financial gain.  It has been concluded through recent publications, art historians, conservators, curators, etc. that roughly 20-50% of all artwork in the world are fakes, forgeries, misattributions, or unknowns.  Albeit a shockingly high number, the art world can now play host to non-invasive technologies to ensure authenticity with methods that guarantee the artwork is preserved in its entirety. 

  1.     Deep Learning

             One of the many methods of validating authenticity is via “Deep Learning”.  By combining machine intelligence with existing human intelligence, the concept of Deep Learning can be implemented.  Rutgers Art and Artificial Intelligence Laboratory Department of Computer Science have been steamrolling the research of anti-forgery through these methods.  See attached link to further understand the promising future of Deep Learning that will use AI to detect art fraud.  Rutgers AAI Lab Digital Humanities Laboratory at Rutgers

Deep Learning
Examples of images generated by the system after trained on 80K paintings from the 15th century to 20th century and forced to deviate from established styles.

  1.    Embedding Synthetic DNA

             Another method being used to prevent fraudulent artwork is through Embed Synthetic DNA. Each artwork is inconspicuously tagged with a unique strand of bioengineered material that provides an encrypted link between the artwork and a secure database containing the definitive information about the artwork.  The startup company, Tagsmart, has stated that these “tags” are specific to the individual art piece making them fully unique and impossible to replicate. They are also claimed to be tamper-proof and affordable.  If the tag is tampered with, as a layer of security, it would become ineffective.  For more information on Tagsmart and other great articles, see the article from ArtNet News. This practice will not only help future creations, but also will be applied to existing art that has been confirmed to be authentic.  

Tagsmart tag

The smart tags include over 20 security features. Photo: courtesy of Tagsmart  


  1.    LEDµSF - Portable Spectrofluorometer 

            One of the most exciting Anti-Forgery devices available on the market today is the LEDµSF, a portable and lightweight spectrofluorometer.  The LEDµSF is a new device that is essential to answer critical questions during the scientific analysis of authenticating highly sought-after artwork.  This technology uses UV fluorescence with exchangeable LED sources to analyze organic and inorganic material which can expand the study and understanding of cultural artwork history.  With a database of reference spectra containing pigments and binders; this device takes contactless, non-invasive, and non-destructive measurements to deliver immediate results.  For more information on this new technology, please visit this link Rotunda Scientific Technologies

LEDµSF DeviceLEDµSF Analyzing a PaintingLEDµSF Data Report

        While technology is streamlining the intricate details of authenticating art pieces, the knowledge and expertise of the curators, authenticators, conservation scientists, etc., will always be needed.  The possibilities are very exciting when combining the human experts along with the advanced analysis technologies available.


This blog was inspired by the following references:

Elgammal, B. Liu, M. Elhoseiny, M. Mazzone, The 8th International Conference on Computational Creativity (ICCC) 2017.

"CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms"

Henri Neuendorf, ArtNet News - Art World May 15, 2017

“Injecting Your Painting With Synthetic DNA Could End Art Forgery as We Know It”

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