Robust PUF Label Authentication System Synergistically Constructed by Hierarchical Pattern of Self‐assembled Phase‐Separation Encrypted Wrinkle and Deep Learning Model

Abstract With the increasing demand for information security, current anti‐counterfeiting methods not only suffer from issues such as low information density and vulnerability to forgery, but also inherently involve a trade‐off between information capacity and readout methods. This paper reports a high‐security solution using hierarchical pattern with perfect combination of micro self‐wrinkle and nano phase‐separation as physical unclonable function (PUF) labels, which is generated through self‐organization of anthracene‐functionalized poly(styrene‐block‐butadiene‐block‐styrene) (SBS‐CAN) under UV exposure. The double‐layer morphologies formed by the wrinkle and phase separation are adjustable, independent, and stable. The obtained hierarchical PUF labels exhibit random and unique features similar to the minutiae of fingerprints at both micro and nano scales, ensuring a well‐balanced bit uniformity (>0.492), high uniqueness (>0.496), and outstanding reliability (>96%). As a consequence of the multi‐layered combination of morphologies, the designed PUF label possesses an information density about 10¹⁰ times higher than that of human fingerprints. The PUF labels can be quickly obtained through simple visual scanning and exhibit sufficient security. To cope with various application environments, the advanced authentication pipeline designed LPLA guarantees robust label recognition capability in real‐world scenarios. A practical integrated anti‐counterfeiting authentication system is developed by combining hierarchical PUF labels and authentication pipeline.