Robust and High-Secured Watermarking System Using Zernike Moments

ABSTRACT: Watermarking is an effective technology that solves many problems within a digitization project. A high capacity data entrenching scheme based on precise and fast framework for the computation of Zernike moments (ZMs) is proposed in this paper. The high capacity is achieved by maximizing data entrenching size and improving the hiding ratio after dipping the inaccuracies in the computation of ZMs. Furthermore, a concept of conditional quantization technique which enables to reduce the total number of ZMs needed to be modified during watermark embedding. Conditional quantization technique concept enhances the visual imperceptibility of the watermarked image and its robustness against various at tacks

Detecting Copy-Move Forgery in Digital Images:A Survey and Analysis of Current Methods

As one of the most successful applications of image analysis and understanding, digital image forgery detection has recently received significant attention, especially during the past few years. At least two trend account for this: the first accepting digital image as official document has become a common practice, and the second the availability of low cost technology in which the image could be easily manipulated. Even though there are many systems to detect the digital image forgery, their success is limited by the conditions imposed by many applications. For example, detecting duplicated region that have been rotated in different angles remains largely unsolved problem. In an attempt to assist these efforts, this paper surveys the recent development in the field of Copy-Move digital image forgery detection

SVD Audio Watermarking: A Tool to Enhance the Security of Image Transmission over ZigBee Networks, Journal of Telecommunications and Information Technology, 2011, nr 4

The security is important issue in wireless networks. This paper discusses audio watermarking as a tool to improve the security of image communication over the IEEE 802.15.4 ZigBee network. The adopted watermarking method implements the Singular-Value Decomposition (SVD) mathematical technique. This method is based on embedding a chaotic encrypted image in the Singular Values (SVs) of the audio signal after transforming it into a 2-D format. The objective of chaotic encryption is to enhance the level of security and resist different attacks. Experimental results show that the SVD audio watermarking method maintains the high quality of the audio signals and that the watermark extraction and decryption are possible even in the presence of attacks over the ZigBee network

Local Geometric Distortions Resilient Watermarking Scheme Based on Symmetry

As an efficient watermark attack method, geometric distortions destroy the synchronization between watermark encoder and decoder. And the local geometric distortion is a famous challenge in the watermark field. Although a lot of geometric distortions resilient watermarking schemes have been proposed, few of them perform well against local geometric distortion like random bending attack (RBA). To address this problem, this paper proposes a novel watermark synchronization process and the corresponding watermarking scheme. In our scheme, the watermark bits are represented by random patterns. The message is encoded to get a watermark unit, and the watermark unit is flipped to generate a symmetrical watermark. Then the symmetrical watermark is embedded into the spatial domain of the host image in an additive way. In watermark extraction, we first get the theoretically mean-square error minimized estimation of the watermark. Then the auto-convolution function is applied to this estimation to detect the symmetry and get a watermark units map. According to this map, the watermark can be accurately synchronized, and then the extraction can be done. Experimental results demonstrate the excellent robustness of the proposed watermarking scheme to local geometric distortions, global geometric distortions, common image processing operations, and some kinds of combined attacks

Accurate Prediction of ncRNA-Protein Interactions From the Integration of Sequence and Evolutionary Information

Non-coding RNA (ncRNA) plays a crucial role in numerous biological processes including gene expression and post-transcriptional gene regulation. The biological function of ncRNA is mostly realized by binding with related proteins. Therefore, an accurate understanding of interactions between ncRNA and protein has a significant impact on current biological research. The major challenge at this stage is the waste of a great deal of redundant time and resource consumed on classification in traditional interaction pattern prediction methods. Fortunately, an efficient classifier named LightGBM can solve this difficulty of long time consumption. In this study, we employed LightGBM as the integrated classifier and proposed a novel computational model for predicting ncRNA and protein interactions. More specifically, the pseudo-Zernike Moments and singular value decomposition algorithm are employed to extract the discriminative features from protein and ncRNA sequences. On four widely used datasets RPI369, RPI488, RPI1807, and RPI2241, we evaluated the performance of LGBM and obtained an superior performance with AUC of 0.799, 0.914, 0.989, and 0.762, respectively. The experimental results of 10-fold cross-validation shown that the proposed method performs much better than existing methods in predicting ncRNA-protein interaction patterns, which could be used as a useful tool in proteomics research

A Localized Geometric-Distortion Resilient Digital Watermarking Scheme Using Two Kinds of Complementary Feature Points

With the rapid development of digital multimedia and internet techniques in the last few years, more and more digital images are being distributed to an ever-growing number of people for sharing, studying, or other purposes. Sharing images digitally is fast and cost-efficient thus highly desirable. However, most of those digital products are exposed without any protection. Thus, without authorization, such information can be easily transferred, copied, and tampered with by using digital multimedia editing software. Watermarking is a popular resolution to the strong need of copyright protection of digital multimedia. In the image forensics scenario, a digital watermark can be used as a tool to discriminate whether original content is tampered with or not. It is embedded on digital images as an invisible message and is used to demonstrate the proof by the owner. In this thesis, we propose a novel localized geometric-distortion resilient digital watermarking scheme to embed two invisible messages to images. Our proposed scheme utilizes two complementary watermarking techniques, namely, local circular region (LCR)-based techniques and block discrete cosine transform (DCT)-based techniques, to hide two pseudo-random binary sequences in two kinds of regions and extract these two sequences from their individual embedding regions. To this end, we use the histogram and mean statistically independent of the pixel position to embed one watermark in the LCRs, whose centers are the scale invariant feature transform (SIFT) feature points themselves that are robust against various affine transformations and common image processing attacks. This watermarking technique combines the advantages of SIFT feature point extraction, local histogram computing, and blind watermark embedding and extraction in the spatial domain to resist geometric distortions. We also use Watson’s DCT-based visual model to embed the other watermark in several rich textured 80×80 regions not covered by any embedding LCR. This watermarking technique combines the advantages of Harris feature point extraction, triangle tessellation and matching, the human visual system (HVS), the spread spectrum-based blind watermark embedding and extraction. The proposed technique then uses these combined features in a DCT domain to resist common image processing attacks and to reduce the watermark synchronization problem at the same time. These two techniques complement each other and therefore can resist geometric and common image processing attacks robustly. Our proposed watermarking approach is a robust watermarking technique that is capable of resisting geometric attacks, i.e., affine transformation (rotation, scaling, and translation) attacks and other common image processing (e.g., JPEG compression and filtering operations) attacks. It demonstrates more robustness and better performance as compared with some peer systems in the literature

Trustworthy authentication on scalable surveillance video with background model support

H.264/SVC (Scalable Video Coding) codestreams, which consist of a single base layer and multiple enhancement layers, are designed for quality, spatial, and temporal scalabilities. They can be transmitted over networks of different bandwidths and seamlessly accessed by various terminal devices. With a huge amount of video surveillance and various devices becoming an integral part of the security infrastructure, the industry is currently starting to use the SVC standard to process digital video for surveillance applications such that clients with different network bandwidth connections and display capabilities can seamlessly access various SVC surveillance (sub)codestreams. In order to guarantee the trustworthiness and integrity of received SVC codestreams, engineers and researchers have proposed several authentication schemes to protect video data. However, existing algorithms cannot simultaneously satisfy both efficiency and robustness for SVC surveillance codestreams. Hence, in this article, a highly efficient and robust authentication scheme, named TrustSSV (Trust Scalable Surveillance Video), is proposed. Based on quality/spatial scalable characteristics of SVC codestreams, TrustSSV combines cryptographic and content-based authentication techniques to authenticate the base layer and enhancement layers, respectively. Based on temporal scalable characteristics of surveillance codestreams, TrustSSV extracts, updates, and authenticates foreground features for each access unit dynamically with background model support. Using SVC test sequences, our experimental results indicate that the scheme is able to distinguish between content-preserving and content-changing manipulations and to pinpoint tampered locations. Compared with existing schemes, the proposed scheme incurs very small computation and communication costs.</jats:p