2 research outputs found
Low-Cost Anti-Copying 2D Barcode by Exploiting Channel Noise Characteristics
In this paper, for overcoming the drawbacks of the prior approaches, such as
low generality, high cost, and high overhead, we propose a Low-Cost
Anti-Copying (LCAC) 2D barcode by exploiting the difference between the noise
characteristics of legal and illegal channels. An embedding strategy is
proposed, and for a variant of it, we also make the corresponding analysis. For
accurately evaluating the performance of our approach, a theoretical model of
the noise in an illegal channel is established by using a generalized Gaussian
distribution. By comparing with the experimental results based on various
printers, scanners, and a mobile phone, it can be found that the sample
histogram and curve fitting of the theoretical model match well, so it can be
concluded that the theoretical model works well. For evaluating the security of
the proposed LCAC code, besides the direct-copying (DC) attack, the improved
version, which is the synthesized-copying (SC) attack, is also considered in
this paper. Based on the theoretical model, we build a prediction function to
optimize the parameters of our approach. The parameters optimization
incorporates the covertness requirement, the robustness requirement and a
tradeoff between the production cost and the cost of illegally-copying attacks
together. The experimental results show that the proposed LCAC code with two
printers and two scanners can detect the DC attack effectively and resist the
SC attack up to the access of 14 legal copies
On Microstructure Estimation Using Flatbed Scanners for Paper Surface Based Authentication
Paper surfaces under the microscopic view are observed to be formed by
intertwisted wood fibers. Such structures of paper surfaces are unique from one
location to another and are almost impossible to duplicate. Previous work used
microscopic surface normals to characterize such intrinsic structures as a
"fingerprint" of paper for security and forensic applications. In this work, we
examine several key research questions of feature extraction in both scientific
and engineering aspects to facilitate the deployment of paper surface-based
authentication when flatbed scanners are used as the acquisition device. We
analytically show that, under the unique optical setup of flatbed scanners, the
specular reflection does not play a role in norm map estimation. We verify,
using a larger dataset than prior work, that the scanner-acquired norm maps,
although blurred, are consistent with those measured by confocal microscopes.
We confirm that, when choosing an authentication feature, high
spatial-frequency subbands of the heightmap are more powerful than the norm
map. Finally, we show that it is possible to empirically calculate the physical
dimensions of the paper patch needed to achieve a certain authentication
performance in equal error rate (EER). We analytically show that log(EER) is
decreasing linearly in the edge length of a paper patch.Comment: This paper is published in IEEE Transactions on Information Forensics
and Securit