With the increasing prevalent of digital devices and their abuse for digital content creation, forgeries of digital images and video footage are more rampant than ever. Digital forensics is challenged into seeking advanced technologies for forgery content detection and acquisition device identification. Unfortunately, existing solutions that address image tampering problems fail to identify the device that produces the images or footage while techniques that can identify the camera is incapable of locating the tampered content of its captured images. In this paper, a new perceptual data-device hash is proposed to locate maliciously tampered image regions and identify the source camera of the received image data as a non-repudiable attestation in digital forensics. The presented image may have been either tampered or gone through benign content preserving geometric transforms or image processing operations. The proposed image hash is generated by projecting the invariant image features into a physical unclonable function (PUF)-defined Bernoulli random space. The tamper-resistant random PUF response is unique for each camera and can only be generated upon triggered by a challenge, which is provided by the image acquisition timestamp. The proposed hash is evaluated on the modified CASIA database and CMOS image sensor-based PUF simulated using 180 nm TSMC technology. It achieves a high tamper detection rate of 95.42% with the regions of tampered content successfully located, a good authentication performance of above 98.5% against standard content-preserving manipulations, and 96.25% and 90.42%, respectively, for the more challenging geometric transformations of rotation (0 ~ 360°) and scaling (scale factor in each dimension: 0.5). It is demonstrated to be able to identify the source camera with 100% accuracy and is secure against attacks on PUF.

中文翻译：

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用于篡改图像检测和源相机识别的基于 PUF 的数据设备哈希


随着数字设备的日益普及及其对数字内容创作的滥用，数字图像和视频片段的伪造比以往任何时候都更加猖獗。数字取证面临的挑战是寻求用于伪造内容检测和采集设备识别的先进技术。不幸的是，解决图像篡改问题的现有解决方案无法识别产生图像或镜头的设备，而可以识别相机的技术无法定位其捕获的图像的篡改内容。在本文中，提出了一种新的感知数据设备哈希来定位恶意篡改的图像区域，并识别接收到的图像数据的源相机，作为数字取证中不可否认的证明。所呈现的图像可能已被篡改或经过良性内容保留几何变换或图像处理操作。所提出的图像哈希是通过将不变图像特征投影到物理不可克隆函数（PUF）定义的伯努利随机空间中来生成的。防篡改随机 PUF 响应对于每个相机来说都是唯一的，并且只能在由图像采集时间戳提供的质询触发时生成。所提出的哈希值在修改后的 CASIA 数据库和使用 180 nm TSMC 技术模拟的基于 CMOS 图像传感器的 PUF 上进行了评估。它实现了 95.42% 的高篡改检测率，成功定位了被篡改内容的区域，针对标准内容保留操作的良好身份验证性能超过 98.5%，对于更具挑战性的几何变换，分别为 96.25% 和 90.42%。旋转（0 ~ 360°）和缩放（每个维度的比例因子：0.5）。 事实证明，它能够以 100% 的准确度识别源相机，并且能够抵御 PUF 的攻击。