论文标题
关于相机指纹估计的信息泄漏
On the Information Leakage of Camera Fingerprint Estimates
论文作者
论文摘要
基于传感器光响应非均匀性（PRNU）的摄像头指纹在法医应用中获得了广泛的知名度，因为它们能够单次识别捕获特定图像的相机。通过某种估计方法提取了给定传感器的指纹，该方法需要一些已知使用此传感器拍摄的图像。在本文中，我们表明以这种方式提取的指纹泄漏了估计中使用的图像的大量信息，从而构成了对隐私的潜在威胁。我们建议通过两种措施量化泄漏：一个基于相互信息，另一个基于成员推理测试的输出。在现实世界图像数据集上使用实用指纹估计器进行实践的实验证实了我们的措施的有效性，并强调了泄漏的严重性以及实施技术来减轻它的重要性。这些技术中的一些进行了简短讨论。
Camera fingerprints based on sensor PhotoResponse Non-Uniformity (PRNU) have gained broad popularity in forensic applications due to their ability to univocally identify the camera that captured a certain image. This fingerprint of a given sensor is extracted through some estimation method that requires a few images known to be taken with such sensor. In this paper, we show that the fingerprints extracted in this way leak a considerable amount of information from those images used in the estimation, thus constituting a potential threat to privacy. We propose to quantify the leakage via two measures: one based on the Mutual Information, and another based on the output of a membership inference test. Experiments with practical fingerprint estimators on a real-world image dataset confirm the validity of our measures and highlight the seriousness of the leakage and the importance of implementing techniques to mitigate it. Some of these techniques are presented and briefly discussed.
