Theoretical Analysis of Information Watermarking in Wavelet-Based Video Compression

Embedding audio bits into images for transmission of video data alleviates the synchronization problem common in video transmission techniques. We continue work combining audio or other information bits and images into one file using digital watermarking techniques to correct the synchronization problem. The system compresses the file by using wavelet image coefficients and implementing bit plane coding. Our research encompasses incorporating five free variables into the watermark/compression technique. These variables are watermark robustness, number of coding iterations, number of image coefficients, number of watermarked information bits, and number of watermarked error correcting bits. By altering these variables, four measurements of the output change. The measurements are the information bit error rate, the image quality, the bit rate, and the amount of watermarked data. We theoretically demonstrate how the variables impact these measurements. Experimental results on real video data support our theoretical findings. By analyzing each video frame, an automated system is able to choose optimal values of the five variables to meet 5 specified measurement constraints

Advanced Linear Identification Techniques For Signal Processing And Digital Video Broadcasting

Linear identification technique is to linearly embed a piece of unique information into digital media data for the purpose of satisfying specific demands such as identification, annotation, and copyright, etc. We need to consider the quantity and the quality of identification data to be embedded as well as the corresponding interference to the original subject signal. However, there exist no generalized computationally-efficient optimization techniques for linear identification up to now. Therefore, in this dissertation work, we try to theoretically investigate the advanced linear identification techniques and combat the tradeoff problems between the quality of the embedded identification data and the quality of the subject signal. Two particular signal processing and telecommunication applications, namely transmitter identification and digital watermarking, will be exploited in this work. We propose a novel optimization paradigm for both digital terrestrial television (DTV) systems and multiple digital watermarking systems to maximize the overall signal-to-interference-plus-noise ratio (SINR) over both identification and subject signals. The new theories and practice related to pseudo random sequences, extended arithmetic-geometric mean inequality, and constrained overall system performance are also presented in this dissertation

A contrast-sensitive reversible visible image watermarking technique

A reversible (also called lossless, distortion-free, or invertible) visible watermarking scheme is proposed to satisfy the applications, in which the visible watermark is expected to combat copyright piracy but can be removed to losslessly recover the original image. We transparently reveal the watermark image by overlapping it on a user-specified region of the host image through adaptively adjusting the pixel values beneath the watermark, depending on the human visual system-based scaling factors. In order to achieve reversibility, a reconstruction/ recovery packet, which is utilized to restore the watermarked area, is reversibly inserted into non-visibly-watermarked region. The packet is established according to the difference image between the original image and its approximate version instead of its visibly watermarked version so as to alleviate its overhead. For the generation of the approximation, we develop a simple prediction technique that makes use of the unaltered neighboring pixels as auxiliary information. The recovery packet is uniquely encoded before hiding so that the original watermark pattern can be reconstructed based on the encoded packet. In this way, the image recovery process is carried out without needing the availability of the watermark. In addition, our method adopts data compression for further reduction in the recovery packet size and improvement in embedding capacity. The experimental results demonstrate the superiority of the proposed scheme compared to the existing methods

Privacy-preserving information hiding and its applications

The phenomenal advances in cloud computing technology have raised concerns about data privacy. Aided by the modern cryptographic techniques such as homomorphic encryption, it has become possible to carry out computations in the encrypted domain and process data without compromising information privacy. In this thesis, we study various classes of privacy-preserving information hiding schemes and their real-world applications for cyber security, cloud computing, Internet of things, etc. Data breach is recognised as one of the most dreadful cyber security threats in which private data is copied, transmitted, viewed, stolen or used by unauthorised parties. Although encryption can obfuscate private information against unauthorised viewing, it may not stop data from illegitimate exportation. Privacy-preserving Information hiding can serve as a potential solution to this issue in such a manner that a permission code is embedded into the encrypted data and can be detected when transmissions occur. Digital watermarking is a technique that has been used for a wide range of intriguing applications such as data authentication and ownership identification. However, some of the algorithms are proprietary intellectual properties and thus the availability to the general public is rather limited. A possible solution is to outsource the task of watermarking to an authorised cloud service provider, that has legitimate right to execute the algorithms as well as high computational capacity. Privacypreserving Information hiding is well suited to this scenario since it is operated in the encrypted domain and hence prevents private data from being collected by the cloud. Internet of things is a promising technology to healthcare industry. A common framework consists of wearable equipments for monitoring the health status of an individual, a local gateway device for aggregating the data, and a cloud server for storing and analysing the data. However, there are risks that an adversary may attempt to eavesdrop the wireless communication, attack the gateway device or even access to the cloud server. Hence, it is desirable to produce and encrypt the data simultaneously and incorporate secret sharing schemes to realise access control. Privacy-preserving secret sharing is a novel research for fulfilling this function. In summary, this thesis presents novel schemes and algorithms, including: • two privacy-preserving reversible information hiding schemes based upon symmetric cryptography using arithmetic of quadratic residues and lexicographic permutations, respectively. • two privacy-preserving reversible information hiding schemes based upon asymmetric cryptography using multiplicative and additive privacy homomorphisms, respectively. • four predictive models for assisting the removal of distortions inflicted by information hiding based respectively upon projection theorem, image gradient, total variation denoising, and Bayesian inference. • three privacy-preserving secret sharing algorithms with different levels of generality

Fast Fragile Watermark Embedding and Iterative Mechanism With High Self-Restoration Performance

This paper presents a new algorithm to reduce significantly the computational cost of one of the best methods with self-recovery capabilities in the fragile watermarking literature. This is achieved by generating two sequences of reference bits associated to the 5 most significant bit-planes (MSBPs) of the image. The reference bits and some authentication bits are then allocated to the 3 least significant bit-planes (LSBPs) of the image. The receiver uses the authentication bits to localise altered pixel-blocks and then executes an iterative restoration mechanism to calculate the original value of the watermarked pixels. Experimental results demonstrate that the embedding method executes significantly faster compared to the state-of-the-art method while achieving a high restoration performance

Dynamic block encryption with self-authenticating key exchange

One of the greatest challenges facing cryptographers is the mechanism used for key exchange. When secret data is transmitted, the chances are that there may be an attacker who will try to intercept and decrypt the message. Having done so, he/she might just gain advantage over the information obtained, or attempt to tamper with the message, and thus, misguiding the recipient. Both cases are equally fatal and may cause great harm as a consequence. In cryptography, there are two commonly used methods of exchanging secret keys between parties. In the first method, symmetric cryptography, the key is sent in advance, over some secure channel, which only the intended recipient can read. The second method of key sharing is by using a public key exchange method, where each party has a private and public key, a public key is shared and a private key is kept locally. In both cases, keys are exchanged between two parties. In this thesis, we propose a method whereby the risk of exchanging keys is minimised. The key is embedded in the encrypted text using a process that we call `chirp coding', and recovered by the recipient using a process that is based on correlation. The `chirp coding parameters' are exchanged between users by employing a USB flash memory retained by each user. If the keys are compromised they are still not usable because an attacker can only have access to part of the key. Alternatively, the software can be configured to operate in a one time parameter mode, in this mode, the parameters are agreed upon in advance. There is no parameter exchange during file transmission, except, of course, the key embedded in ciphertext. The thesis also introduces a method of encryption which utilises dynamic blocks, where the block size is different for each block. Prime numbers are used to drive two random number generators: a Linear Congruential Generator (LCG) which takes in the seed and initialises the system and a Blum-Blum Shum (BBS) generator which is used to generate random streams to encrypt messages, images or video clips for example. In each case, the key created is text dependent and therefore will change as each message is sent. The scheme presented in this research is composed of five basic modules. The first module is the key generation module, where the key to be generated is message dependent. The second module, encryption module, performs data encryption. The third module, key exchange module, embeds the key into the encrypted text. Once this is done, the message is transmitted and the recipient uses the key extraction module to retrieve the key and finally the decryption module is executed to decrypt the message and authenticate it. In addition, the message may be compressed before encryption and decompressed by the recipient after decryption using standard compression tools

AN EFFECTIVE REVERSIBLE DATA HIDING METHOD BASED ON PIXEL-VALUE-ORDERING

This paper presents a new effective reversible data hiding method based on pixel-value-ordering (iGePVO-K) which is improvement of a recent GePVO-K method that recently is considered as a PVO-used method having highest embedding capacity. In comparison with GePVO-K method, iGePVO-K has the following advantages. First, the embedding capacity of the new method is higher than that of GePVO-K method by using data embedding formulas reasonably and reducing the location map size. Second, for embedding data, in the new method, each pixel value is modified at most by one, while in GePVO-K method, each pixel value may be modified by two. In fact, in the GePVO-K method, the largest pixels are modified by two for embedding bits 1 and by one for bits 0. This is also true for the smallest pixels. Meanwhile, in the proposed method, the largest pixels are modified by one for embedding bits 1 and are unchanged if embedding bits 0. Therefore, the stego-image quality in proposed method is better than that in GePVO-K method. Theoretical analysis and experiment results show that the proposed method has higher embedding capacity and better stego image quality than GePVO-K method

Wavelet techniques for reversible data embedding into images

The proliferation of digital information in our society has enticed a lot of research into data embedding techniques that add information to digital content like images, audio and video. This additional information can be used for various purposes and different applications place different requirements on the embedding techniques. In this paper, we investigate high capacity lossless data embedding methods that allow one to embed large amounts of data into digital images (or video) in such a way that the original image can be reconstructed from the watermarked image. The paper starts by briefly reviewing three existing lossless data embedding techniques as described by Fridrich and co-authors, by Tian, and by Celik and co-workers. We then present two new techniques: one based on least significant bit prediction and Sweldens' lifting scheme and another that is an improvement of Tian's technique of difference expansion. The various embedding methods are then compared in terms of capacity-distortion behaviour, embedding speed, and capacity control