Data hiding in multimedia - theory and applications

Multimedia data hiding or steganography is a means of communication using subliminal channels. The resource for the subliminal communication scheme is the distortion of the original content that can be tolerated. This thesis addresses two main issues of steganographic communication schemes: 1. How does one maximize the distortion introduced without affecting fidelity of the content? 2. How does one efficiently utilize the resource (the distortion introduced) for communicating as many bits of information as possible? In other words, what is a good signaling strategy for the subliminal communication scheme? Close to optimal solutions for both issues are analyzed. Many techniques for the issue for maximizing the resource, viz, the distortion introduced imperceptibly in images and video frames, are proposed. Different signaling strategies for steganographic communication are explored, and a novel signaling technique employing a floating signal constellation is proposed. Algorithms for optimal choices of the parameters of the signaling technique are presented. Other application specific issues like the type of robustness needed are taken into consideration along with the established theoretical background to design optimal data hiding schemes. In particular, two very important applications of data hiding are addressed - data hiding for multimedia content delivery, and data hiding for watermarking (for proving ownership). A robust watermarking protocol for unambiguous resolution of ownership is proposed

Natural Image Statistics for Digital Image Forensics

We describe a set of natural image statistics that are built upon two multi-scale image decompositions, the quadrature mirror filter pyramid decomposition and the local angular harmonic decomposition. These image statistics consist of first- and higher-order statistics that capture certain statistical regularities of natural images. We propose to apply these image statistics, together with classification techniques, to three problems in digital image forensics: (1) differentiating photographic images from computer-generated photorealistic images, (2) generic steganalysis; (3) rebroadcast image detection. We also apply these image statistics to the traditional art authentication for forgery detection and identification of artists in an art work. For each application we show the effectiveness of these image statistics and analyze their sensitivity and robustness

Mitigation of H.264 and H.265 Video Compression for Reliable PRNU Estimation

The photo-response non-uniformity (PRNU) is a distinctive image sensor characteristic, and an imaging device inadvertently introduces its sensor's PRNU into all media it captures. Therefore, the PRNU can be regarded as a camera fingerprint and used for source attribution. The imaging pipeline in a camera, however, involves various processing steps that are detrimental to PRNU estimation. In the context of photographic images, these challenges are successfully addressed and the method for estimating a sensor's PRNU pattern is well established. However, various additional challenges related to generation of videos remain largely untackled. With this perspective, this work introduces methods to mitigate disruptive effects of widely deployed H.264 and H.265 video compression standards on PRNU estimation. Our approach involves an intervention in the decoding process to eliminate a filtering procedure applied at the decoder to reduce blockiness. It also utilizes decoding parameters to develop a weighting scheme and adjust the contribution of video frames at the macroblock level to PRNU estimation process. Results obtained on videos captured by 28 cameras show that our approach increases the PRNU matching metric up to more than five times over the conventional estimation method tailored for photos

Steganography A Data Hiding Technique

Steganography implements an encryption technique in which communication takes place by hiding information. A hidden message is the combination of a secret message with the carrier message. This technique can be used to hide the message in an image, a video file, an audio file or in a file system. There are large variety of steganography techniques that will be used for hiding secret information in images. The final output image is called as a stego-image which consists of a secret message or information. Imperceptibility, payload, and robustness are three most important parameters for audio steganography. For a more secure approach, encryption can be used, which will encrypt the secret message using a secret key and then sent to the receiver. The receiver after receiving the message then decrypts the secret message to obtain the original one. In this paper, compared steganography with cryptography, which is an encrypting technique and explained how steganography provides better security in terms of hiding the secret message. In this paper, the various techniques are illustrated, which are used in steganography and studying the implementation of those techniques. Also, demonstrated the implementation process of one of the steganography techniques. A comparative analysis is performed between various steganographic tools by using the sample test images and test data. The quality metrics such as PSNR and SSIM are calculated for the final output images which are used for rating the tools. This paper also discusses about the Steganalysis which is known as the process of identifying the use of steganography