论文标题
盲目检测伪造副本检测模式的印刷成像渠道的数学模型
Mathematical model of printing-imaging channel for blind detection of fake copy detection patterns
论文作者
论文摘要
如今，复制检测模式（CDP）似乎是一种非常有前途的反爆炸技术，用于物理对象保护。但是，深度学习作为一种强大的攻击工具的出现表明，一般身份验证方案无法竞争并在此类攻击中失败。在本文中，我们为CDP身份验证以及基于IT的新检测方案提出了一个新的印刷成像通道数学模型。结果表明，即使是深度学习创建的副本在培训阶段都无法根据所提出的方法可靠地进行身份验证，并且在身份验证期间仅使用CDP的数字参考。
Nowadays, copy detection patterns (CDP) appear as a very promising anti-counterfeiting technology for physical object protection. However, the advent of deep learning as a powerful attacking tool has shown that the general authentication schemes are unable to compete and fail against such attacks. In this paper, we propose a new mathematical model of printing-imaging channel for the authentication of CDP together with a new detection scheme based on it. The results show that even deep learning created copy fakes unknown at the training stage can be reliably authenticated based on the proposed approach and using only digital references of CDP during authentication.
