Digital image forensics

Digital image forensics is a relatively new research field that aims to expose the origin and composition of, and the history of processing applied to digital images. Hence, the digital image forensics is expected to be of significant importance to our modern society in which the digital media are getting more and more popular. In this thesis, image tampering detection and classification of double JPEG compression are the two major subjects studied. Since any manipulation applied to digital images changes image statistics, identifying statistical artifacts becomes critically important in image forensics. In this thesis, a few typical forensic techniques have been studied. Finally, it is foreseen that the investigations on endless confliction between forensics and anti-forensics are to deepen our understanding on image statistics and advance civilization of our society

An Image Forensic Scheme with Robust and Fragile Watermarking for Business Documents

This paper proposes an image forensic scheme with both robust and fragile watermarking techniques for business documents. Through a dual watermarking approach, the proposed scheme can achieve image forensics objectives of (a) identification of source; (b) authentication of documents; and (c) locating the tempered areas of documents due to attacks. An example is presented to prove the concepts of the proposed scheme. Keywords: Image Forensics, Fragile and Robust Watermarking, Business Document

An Evaluation Framework For Digital Image Forensics Tools

The boom of digital cameras, photography, and social media has drastically changed how humans live their day-to-day, but this normalization is accompanied by malicious agents finding new ways to forge and tamper with images for unlawful monetary (or other) gains. Disinformation in the photographic media realm is an urgent threat. The availability of a myriad of image editing tools renders it almost impossible to differentiate between photo-realistic and original images. The tools available for image forensics require a standard framework against which they can be evaluated. Such a standard framework can aid in evaluating the suitability of an image forensics tool for use in a criminal investigation, commercial operation, or academic research. This paper proposes an evaluation framework designed for image forensics tools based on the conformance methodology of testing that employs test assertions and test cases. It is then used to evaluate four image forensics tools namely FotoForensics, Ghiro, Imago Forensics, and Exif Reader. The comparative insight of test results produced by the framework provides a ground for ranking the tools from best to least comprehensive. The results also provide information necessary for users to make intelligent choices about tools and help vendors shortlist areas of improvement in their tools

Color-decoupled photo response non-uniformity for digital image forensics

The last few years have seen the use of photo response non-uniformity noise (PRNU), a unique fingerprint of imaging sensors, in various digital forensic applications such as source device identification, content integrity verification and authentication. However, the use of a colour filter array for capturing only one of the three colour components per pixel introduces colour interpolation noise, while the existing methods for extracting PRNU provide no effective means for addressing this issue. Because the artificial colours obtained through the colour interpolation process is not directly acquired from the scene by physical hardware, we expect that the PRNU extracted from the physical components, which are free from interpolation noise, should be more reliable than that from the artificial channels, which carry interpolation noise. Based on this assumption we propose a Couple-Decoupled PRNU (CD-PRNU) extraction method, which first decomposes each colour channel into 4 sub-images and then extracts the PRNU noise from each sub-image. The PRNU noise patterns of the sub-images are then assembled to get the CD-PRNU. This new method can prevent the interpolation noise from propagating into the physical components, thus improving the accuracy of device identification and image content integrity verification