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Nowadays, the field of physical object security based on surface microstructures lacks common and shared data for the development, testing and fair benchmarking of new identification and authentication technologies. To our knowledge, most published results are based on proprietary data that also often lacks the necessary size for statistically significant results and conclusions. Therefore, in this paper, we introduce the first publicly available documented database for the investigation of physical object authentication based on non-cloneable surface microstructure images. We have built an automatic system suitable for massive acquisition of microstructure images from flat surfaces under different light conditions and with different cameras. The samples are acquired several times, and resulting images are aligned, labelled and online available to the public for further investigation and benchmarking of new methods. In this paper, we present the statistical properties for the images originating from 5000 unique carton packages acquired 6 times each with two different cameras. Furthermore, we derive statistical authentication frameworks for the original, the random projected and binarized domains presented together with all empirical results.