Digital Multimedia Forensics and Anti-Forensics

As the use of digital multimedia content such as images and video has increased, so has the means and the incentive to create digital forgeries. Presently, powerful editing software allows forgers to create perceptually convincing digital forgeries. Accordingly, there is a great need for techniques capable of authenticating digital multimedia content. In response to this, researchers have begun developing digital forensic techniques capable of identifying digital forgeries. These forensic techniques operate by detecting imperceptible traces left by editing operations in digital multimedia content. In this dissertation, we propose several new digital forensic techniques to detect evidence of editing in digital multimedia content. We begin by identifying the fingerprints left by pixel value mappings and show how these can be used to detect the use of contrast enhancement in images. We use these fingerprints to perform a number of additional forensic tasks such as identifying cut-and-paste forgeries, detecting the addition of noise to previously JPEG compressed images, and estimating the contrast enhancement mapping used to alter an image. Additionally, we consider the problem of multimedia security from the forger's point of view. We demonstrate that an intelligent forger can design anti-forensic operations to hide editing fingerprints and fool forensic techniques. We propose an anti-forensic technique to remove compression fingerprints from digital images and show that this technique can be used to fool several state-of-the-art forensic algorithms. We examine the problem of detecting frame deletion in digital video and develop both a technique to detect frame deletion and an anti-forensic technique to hide frame deletion fingerprints. We show that this anti-forensic operation leaves behind fingerprints of its own and propose a technique to detect the use of frame deletion anti-forensics. The ability of a forensic investigator to detect both editing and the use of anti-forensics results in a dynamic interplay between the forger and forensic investigator. We use develop a game theoretic framework to analyze this interplay and identify the set of actions that each party will rationally choose. Additionally, we show that anti-forensics can be used protect against reverse engineering. To demonstrate this, we propose an anti-forensic module that can be integrated into digital cameras to protect color interpolation methods

Reverse engineering of double compressed images in the presence of contrast enhancement

Abstract-A comparison between two forensic techniques for the reverse engineering of a chain composed by a double JPEG compression interleaved by a linear contrast enhancement is presented here. The first approach is based on the well known peak-to-valley behavior of the histogram of double-quantized DCT coefficients, while the second approach is based on the distribution of the first digit of DCT coefficients. These methods have been extended to the study of the considered processing chain, for both the chain detection and the estimation of its parameters. More specifically, the proposed approaches provide an estimation of the quality factor of the previous JPEG compression and the amount of linear contrast enhancement

Image Forensics for Forgery Detection using Contrast Enhancement and 3D Lighting

Nowadays the digital image plays an important role in human life. Due to large growth in the image processing techniques, with the availability of image modification tools any modification in the images can be done. These modifications cannot be recognized by human eyes. So Identification of the image integrity is very important in today’s life. Contrast and brightness of digital images can be adjusted by contrast enhancement. Move and paste type of images are Created by malicious person, in which contrast of one source image is enhanced to match the other source image. Here in this topic contrast enhancement technique is used which aimed at detecting image tampering has grown in different applications area such as law enforcement, surveillance. Also with the contrast enhancement, we propose an improved 3D lighting environment estimation method based on a more general surface reflection model. 3D lighting environment is an important clue in an image that can be used for image forgery detection. We intend to employ fully automatic face morphing and alignment algorithms. Also we intend to use face detection method to detect the face existence and 3D lighting environment estimation to check originality of human faces in the image