  This paper concerns the problem of detecting the use of information hiding at
anti-copying 2D barcodes. Prior hidden information detection schemes are either
heuristicbased or Machine Learning (ML) based. The key limitation of prior
heuristics-based schemes is that they do not answer the fundamental question of
why the information hidden at a 2D barcode can be detected. The key limitation
of prior MLbased information schemes is that they lack robustness because a
printed 2D barcode is very much environmentally dependent, and thus an
information hiding detection scheme trained in one environment often does not
work well in another environment. In this paper, we propose two hidden
information detection schemes at the existing anti-copying 2D barcodes. The
first scheme is to directly use the pixel distance to detect the use of an
information hiding scheme in a 2D barcode, referred as to the Pixel Distance
Based Detection (PDBD) scheme. The second scheme is first to calculate the
variance of the raw signal and the covariance between the recovered signal and
the raw signal, and then based on the variance results, detects the use of
information hiding scheme in a 2D barcode, referred as to the Pixel Variance
Based Detection (PVBD) scheme. Moreover, we design advanced IC attacks to
evaluate the security of two existing anti-copying 2D barcodes. We implemented
our schemes and conducted extensive performance comparison between our schemes
and prior schemes under different capturing devices, such as a scanner and a
camera phone. Our experimental results show that the PVBD scheme can correctly
detect the existence of the hidden information at both the 2LQR code and the
LCAC 2D barcode. Moreover, the probability of successfully attacking of our IC
attacks achieves 0.6538 for the 2LQR code and 1 for the LCAC 2D barcode.
