Paper Information Recording and Security Protection Using Invisible Ink and Artificial Intelligence.

Abstract

Conventional paper information protection mainly relies on stimuli-responsive functional materials that can display color or luminescence under external stimuli; however, this method is rather predictable and can be easily cracked. In this work, a paper information protection scheme combining fluorescent invisible ink and artificial intelligence was proposed. The ink was prepared by dissolving carbon nanoparticles in water, which has a high quantum yield and outstanding light stability and salt stability, thus ensuring the integrity of information in complex environments. A five-layer convolutional neural network (one of the two mainstream architectures in today's artificial intelligence fields) was specially trained based on ultraviolet light excited symbols printed by invisible ink. Using this scheme, the correct information could only be read with the specially trained neural network after ultraviolet (UV) irradiation. Without this trained neural network or UV irradiation, misleading messages will be presented. Moreover, it was possible to design unpredictable and highly complex password books to further increase information security. This smart strategy provides new opportunities for high-level paper information encryption and also proposes new ideas for the applications of carbon nanoparticles and artificial intelligence.