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Authentication of Copy Detection Patterns: A Pattern Reliability Based Approach
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DOI：10.1109/TIFS.2024.3359510.png)
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Copy Detection Pattern (CDP) technology is a promising anti-counterfeiting solution for the protection of physical goods. In recent years, it has been shown that this technology is threatened by powerful deep learning attacks that are able to bypass original authentication schemes. In this paper, we tackle this problem by proposing a new CDP authentication scheme based on statistical knowledge discovered about the printing and imaging process. The novelty of our approach lies in providing means to measure the reliability of each local pattern appearing in the CDP. This allows to define new authentication measures to better differentiate original CDP from fakes. Our results show that this new system is capable of performing reliable CDP authentication with smartphones without the need for heavyweight machine learning tools requiring massive data entries.
Keyword:
Authentication
Reliability
Symbols
Probes
Printing
Imaging
Smart phones
Copy detection patterns
smartphone authentication
binary pattern-based channel
deep learning fakes
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8
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5.3K
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