prnu泄漏:事实和补救措施

F. Pérez-González, Samuel Fernández-Menduiña
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引用次数: 6

摘要

我们解决了传感器的光响应非均匀性(PRNU)指纹估计的信息泄漏问题。这种泄漏可能会损害取证场景中的隐私,因为它可能会泄露PRNU估计中使用的图像中的信息。我们提出了一种基于嵌入合成PRNUs的计算信息论泄漏的新方法,并给出了可承受的近似值和边界。我们还提出了一种新的精简度量方法来衡量隶属推理测试的性能。最后,我们分析了两种潜在的防泄漏对策:二值化和均衡。二值化是一种已经在prnu存储环境中使用的方法,而均衡是一种新颖且性能更好的方法。在实际图像数据集上进行了实验,验证了理论结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PRNU-leaks: facts and remedies
We address the problem of information leakage from estimates of the PhotoResponse Non-Uniformity (PRNU) fingerprints of a sensor. This leakage may compromise privacy in forensic scenarios, as it may reveal information from the images used in the PRNU estimation. We propose a new way to compute the information-theoretic leakage that is based on embedding synthetic PRNUs, and presesent affordable approximations and bounds. We also propose a new compact measure for the performance in membership inference tests. Finally, we analyze two potential countermeasures against leakage: binarization, which was already used in PRNU-storage contexts, and equalization, which is novel and offers better performance. Theoretical results are validated with experiments carried out on a real-world image dataset.
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