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Game theoretic analysis of camera source identification

机译:摄像机源识别的博弈论分析

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摘要

Sensor pattern noise (SPN) is recognized as a reliable device fingerprint for camera source identification (CSI). However, source identification method (source test) ignores whether the fingerprint is forged and anti-forensic techniques seldom consider traces they leave behind. Therefore, the performance of above techniques needs to be evaluated again by assuming the existence of both parties of a forensic investigator and an anti-forensic forger. In this paper, we propose a novel counter anti-forensic method based on noise level estimation to detect the possible forgery (forgery test). Furthermore, we evaluate the Nash equilibrium performance when investigator performs both source test and forgery test, and identify the optimal strategies of both parties with the game theory. The experimental results show that our proposed method can achieve good performance without collecting the candidate image set in the existing triangle test method especially when the false alarm rate is held low (e.g. Pfa < 5%).
机译:传感器图案噪声(SPN)被识别为相机源识别(CSI)的可靠设备指纹。然而,源识别方法(源测试)忽略指纹是否伪造,并且防伪技术很少考虑他们留下的痕迹。因此,通过假设法医调查仪和抗法医伪造者双方存在,需要再次评估上述技术的性能。在本文中,我们提出了一种基于噪声水平估计来检测可能的伪造(伪造测试)的新型计数器反锐利方法。此外,当研究者执行源测试和伪造测试时,我们评估了纳什均衡性能,并确定了博弈论双方的最佳策略。实验结果表明,我们所提出的方法可以实现良好的性能而不收集现有三角形测试方法中设置的候选图像,特别是当误报率低(例如PFA <5%)时。

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