Determining the authenticity of a painting is not an easy task. First, distinguishing fake paintings from originals is challenging, and often even art experts cannot reliably identify forgeries. Counterfeiters can also create spurious documentation to support the “authenticity”
of fake paintings. In this work, we present work toward CanvasChain, a system for authenticating/tracking paintings that uses a blockchain in combination with a robust hash of the crack patterns (craquelure) on the surface of paintings. The robust hash is used as a painting’s fingerprint,
which is used in a blockchain to validate and authenticate the painting. We present an initial realization of CanvasChain using a robust hash based on the BRISK feature descriptor and the neo blockchain, which supports smart contracts for basic required transactions. We present results from
tests conducted on the proposed system to assess both the robust hash and the blockchain. Cost estimates obtained from the prototype realization indicate that the system is cost effective: e.g. it costs approximately US $1.85 to register a painting and benefit from the blockchain. As
future work, we identify additional components required to make CanvasChain a full-fledged solution.