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This paper concerns the problem of detecting the use of information hiding atanti-copying 2D barcodes. Prior hidden information detection schemes are eitherheuristicbased or Machine Learning (ML) based. The key limitation of priorheuristics-based schemes is that they do not answer the fundamental question ofwhy the information hidden at a 2D barcode can be detected. The key limitationof prior MLbased information schemes is that they lack robustness because aprinted 2D barcode is very much environmentally dependent, and thus aninformation hiding detection scheme trained in one environment often does notwork well in another environment. In this paper, we propose two hiddeninformation detection schemes at the existing anti-copying 2D barcodes. Thefirst scheme is to directly use the pixel distance to detect the use of aninformation hiding scheme in a 2D barcode, referred as to the Pixel DistanceBased Detection (PDBD) scheme. The second scheme is first to calculate thevariance of the raw signal and the covariance between the recovered signal andthe raw signal, and then based on the variance results, detects the use ofinformation hiding scheme in a 2D barcode, referred as to the Pixel VarianceBased Detection (PVBD) scheme. Moreover, we design advanced IC attacks toevaluate the security of two existing anti-copying 2D barcodes. We implementedour schemes and conducted extensive performance comparison between our schemesand prior schemes under different capturing devices, such as a scanner and acamera phone. Our experimental results show that the PVBD scheme can correctlydetect the existence of the hidden information at both the 2LQR code and theLCAC 2D barcode. Moreover, the probability of successfully attacking of our ICattacks achieves 0.6538 for the 2LQR code and 1 for the LCAC 2D barcode.

Detection of Information Hiding at Anti-Copying 2D Barcodes