Fundamental Limits in Multimedia Forensics and Anti-forensics

As the use of multimedia editing tools increases, people become questioning the authenticity of multimedia content. This is specially a big concern for authorities, such as law enforcement, news reporter and government, who constantly use multimedia evidence to make critical decisions. To verify the authenticity of multimedia content, many forensic techniques have been proposed to identify the processing history of multimedia content under question. However, as new technologies emerge and more complicated scenarios are considered, the limitation of multimedia forensics has been gradually realized by forensic researchers. It is the inevitable trend in multimedia forensics to explore the fundamental limits. In this dissertation, we propose several theoretical frameworks to study the fundamental limits in various forensic problems. Specifically, we begin by developing empirical forensic techniques to deal with the limitation of existing techniques due to the emergence of new technology, compressive sensing. Then, we go one step further to explore the fundamental limit of forensic performance. Two types of forensic problems have been examined. In operation forensics, we propose an information theoretical framework and define forensicability as the maximum information features contain about hypotheses of processing histories. Based on this framework, we have found the maximum number of JPEG compressions one can detect. In order forensics, an information theoretical criterion is proposed to determine when we can and cannot detect the order of manipulation operations that have been applied on multimedia content. Additionally, we have examined the fundamental tradeoffs in multimedia antiforensics, where attacking techniques are developed by forgers to conceal manipulation fingerprints and confuse forensic investigations. In this field, we have defined concealability as the effectiveness of anti-forensics concealing manipulation fingerprints. Then, a tradeoff between concealability, rate and distortion is proposed and characterized for compression anti-forensics, which provides us valuable insights of how forgers may behave under their best strategy

Wavelet İle Dayanıklı Mpeg Video Damgalama

DergiPark: 245960trakyafbdYarı kör resim damgalama metodu PRN sayılarını DWT HH bant katsayılarından T1 basamağından büyük olanlarına damgalar. Saldırıya uğramış resim katsayıları başlangıç resim ile korelasyon yapılır. Damgayı bulmak için, basamak T2’den (T2 gt; T1 ) büyük olan katsayılar başlangıç resmi ile korelasyon edilir. Bu fikir LL ve HH bantlarına damgalama olarak geliştirilmiştir. Bu makalede ise bu daha önce geliştirdiğimiz bu fikri MPEG videoları için kullandık. Deney sonuçlarımız gösteriyorki bazı saldırılar için LL bantında damgalama, diğer bir grup saldırıda ise HH bantında damgalama daha iyi sonuç vermektedir.A semi-blind image watermarking scheme embeds a pseudo random sequence in all the high pass DWT coefficients above a given threshold T1. The attacked DWT coefficients are then correlated with the original watermark. For watermark detection, all the coefficients higher than another threshold T2 ( gt;T1) are chosen for correlation with the original watermark. This idea was extended to embed the same watermark in two bands (LL and HH). In this paper, we embed a pseudo random sequence in MPEG-1 using two bands (LL and HH). Our experiments show that for one group of attacks (i.e., JPEG compression, Gaussian noise, resizing, low pass filtering, rotation, and frame dropping), the correlation with the real watermark is higher than the threshold in the LL band, and for another group of attacks (i.e., cropping, histogram equalization, contrast adjustment, and gamma correction), the correlation with the real watermark is higher than the threshold in the HH band

An Overview on Image Forensics

The aim of this survey is to provide a comprehensive overview of the state of the art in the area of image forensics. These techniques have been designed to identify the source of a digital image or to determine whether the content is authentic or modified, without the knowledge of any prior information about the image under analysis (and thus are defined as passive). All these tools work by detecting the presence, the absence, or the incongruence of some traces intrinsically tied to the digital image by the acquisition device and by any other operation after its creation. The paper has been organized by classifying the tools according to the position in the history of the digital image in which the relative footprint is left: acquisition-based methods, coding-based methods, and editing-based schemes

Attention Driven Solutions for Robust Digital Watermarking Within Media

As digital technologies have dramatically expanded within the last decade, content recognition now plays a major role within the control of media. Of the current recent systems available, digital watermarking provides a robust maintainable solution to enhance media security. The two main properties of digital watermarking, imperceptibility and robustness, are complimentary to each other but by employing visual attention based mechanisms within the watermarking framework, highly robust watermarking solutions are obtainable while also maintaining high media quality. This thesis firstly provides suitable bottom-up saliency models for raw image and video. The image and video saliency algorithms are estimated directly from within the wavelet domain for enhanced compatibility with the watermarking framework. By combining colour, orientation and intensity contrasts for the image model and globally compensated object motion in the video model, novel wavelet-based visual saliency algorithms are provided. The work extends these saliency models into a unique visual attention-based watermarking scheme by increasing the watermark weighting parameter within visually uninteresting regions. An increased watermark robustness, up to 40%, against various filtering attacks, JPEG2000 and H.264/AVC compression is obtained while maintaining the media quality, verified by various objective and subjective evaluation tools. As most video sequences are stored in an encoded format, this thesis studies watermarking schemes within the compressed domain. Firstly, the work provides a compressed domain saliency model formulated directly within the HEVC codec, utilizing various coding decisions such as block partition size, residual magnitude, intra frame angular prediction mode and motion vector difference magnitude. Large computational savings, of 50% or greater, are obtained compared with existing methodologies, as the saliency maps are generated from partially decoded bitstreams. Finally, the saliency maps formulated within the compressed HEVC domain are studied within the watermarking framework. A joint encoder and a frame domain watermarking scheme are both proposed by embedding data into the quantised transform residual data or wavelet coefficients, respectively, which exhibit low visual salience

Joint watermarking and encryption of color images in the Fibonacci-Haar domain

A novel method for watermarking and ciphering color images, based on the joint use of a key-dependent wavelet transform with a secure cryptographic scheme, is presented. The system allows to watermark encrypted data without requiring the knowledge of the original data and also to cipher watermarked data without damaging the embedded signal. Since different areas of the proposed transform domain are used for encryption and watermarking, the extraction of the hidden information can be performed without deciphering the cover data and it is also possible to decipher watermarked data without removing the watermark. Experimental results show the effectiveness of the proposed scheme

DCT Video Compositing with Embedded Zerotree Coding for Multi-Point Video Conferencing

In this thesis, DCT domain video compositing with embedded zerotree coding for multi-point video conferencing is considered. In a typical video compositing system, video sequences coming from different sources are composited into one video stream and sent using a single channel to the receiver points. There are mainly three stages of video compositing: decoding of incoming video streams, decimation of video frames, andencoding of the composited video. Conventional spatial domain video compositing requires transformations between the DCT and the spatial domains increasing the complexity of computations. The advantage of the DCT domain video compositing is that the decoding, decimation and encoding remain fully in the DCT domain resulting in faster processing time and better quality of the composited videos. The composited videos are encoded via a DCT based embedded zerotree coder which was originally developed for wavelet coding. An adaptive arithmetic coder is used to encode the symbols obtained from the DCT based zerotree codingresulting in embedded bit stream. By using the embedded zerotree coder the quality of the composited videos is improved when compared to a conventional encoder. An advanced versionof zerotree coder is also used to increase the performance of the compositing system. Another improvement is due to the use of local cosine transform to decrease the blocking effect at low bit rates. We also apply the proposed DCT decimation/interpolation for single stream video coding achieving better quality than regular encoding process at low bit rates. The bit rate control problem is easily solved by taking the advantage the embedded property of zerotree coding since the coding control parameter is the bit rate itself. We also achieve the optimum bit rate allocation among the composited frames in a GOP without using subframe layer bit rate allocation, since zerotree coding uses successive approximation quantization allowing DCT coefficients to be encoded in descending significance order

Maximum Energy Subsampling: A General Scheme For Multi-resolution Image Representation And Analysis

Image descriptors play an important role in image representation and analysis. Multi-resolution image descriptors can effectively characterize complex images and extract their hidden information. Wavelets descriptors have been widely used in multi-resolution image analysis. However, making the wavelets transform shift and rotation invariant produces redundancy and requires complex matching processes. As to other multi-resolution descriptors, they usually depend on other theories or information, such as filtering function, prior-domain knowledge, etc.; that not only increases the computation complexity, but also generates errors. We propose a novel multi-resolution scheme that is capable of transforming any kind of image descriptor into its multi-resolution structure with high computation accuracy and efficiency. Our multi-resolution scheme is based on sub-sampling an image into an odd-even image tree. Through applying image descriptors to the odd-even image tree, we get the relative multi-resolution image descriptors. Multi-resolution analysis is based on downsampling expansion with maximum energy extraction followed by upsampling reconstruction. Since the maximum energy usually retained in the lowest frequency coefficients; we do maximum energy extraction through keeping the lowest coefficients from each resolution level. Our multi-resolution scheme can analyze images recursively and effectively without introducing artifacts or changes to the original images, produce multi-resolution representations, obtain higher resolution images only using information from lower resolutions, compress data, filter noise, extract effective image features and be implemented in parallel processing