General Framework of Reversible Watermarking Based on Asymmetric Histogram Shifting of Prediction Error

This paper presents a general framework for the reversible watermarking based on asymmetric histogram shifting of prediction error, which is inspired by reversible watermarking of prediction error. Different from the conventional algorithms using single-prediction scheme to create symmetric histogram, the proposed method employs a multi-prediction scheme, which calculates multiple prediction values for the pixels. Then, the suitable value would be selected by two dual asymmetric selection functions to construct two asymmetric error histograms. Finally, the watermark is embedded in the two error histograms separately utilizing a complementary embedding strategy. The proposed framework provides a new perspective for the research of reversible watermarking, which brings about many benefits for the information security

Reversible difference expansion multi-layer data hiding technique for medical images

Maintaining the privacy and security of confidential information in data communication has always been a major concern. It is because the advancement of information technology is likely to be followed by an increase in cybercrime, such as illegal access to sensitive data. Several techniques were proposed to overcome that issue, for example, by hiding data in digital images. Reversible data hiding is an excellent approach for concealing private data due to its ability to be applied in various fields. However, it yields a limited payload and the quality of the image holding data (Stego image), and consequently, these two factors may not be addressed simultaneously. This paper addresses this problem by introducing a new non-complexity difference expansion (DE) and block-based reversible multi-layer data hiding technique constructed by exploring DE. Sensitive data are embedded into the difference values calculated between the original pixels in each block with relatively low complexity. To improve the payload capacity, confidential data are embedded in multiple layers of grayscale medical images while preserving their quality. The experiment results prove that the proposed technique has increased the payload with an average of 369999 bits and kept the peak signal to noise ratio (PSNR) to the average of 36.506 dB using medical images' adequate security the embedded private data. This proposed method has improved the performance, especially the secret size, without reducing much the quality. Therefore, it is suitable to use for relatively big payloads

Data hiding techniques in steganography using fibonacci sequence and knight tour algorithm

The foremost priority in the information and communication technology era, is achieving an efficient and accurate steganography system for hiding information. The developed system of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography system is the main issue to be addressed. This study proposed an improved for embedding secret message into an image. This newly developed method is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select the pixel before random embedding to select block of (64 × 64) pixels, follows by the Knight Tour algorithm to select sub-block of (8 × 8) pixels, and finally by the random pixels selection. For secret embedding, Fibonacci sequence is implemented to decomposition pixel from 8 bitplane to 12 bitplane. The proposed method is distributed over the entire image to maintain high level of security against any kind of attack. Gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. The results show good PSNR value with high capacity and these findings verified the worthiness of the proposed method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing systems in the literature

An improved image steganography scheme based on distinction grade value and secret message encryption

Steganography is an emerging and greatly demanding technique for secure information communication over the internet using a secret cover object. It can be used for a wide range of applications such as safe circulation of secret data in intelligence, industry, health care, habitat, online voting, mobile banking and military. Commonly, digital images are used as covers for the steganography owing to their redundancy in the representation, making them hidden to the intruders, hackers, adversaries, unauthorized users. Still, any steganography system launched over the Internet can be cracked upon recognizing the stego cover. Thus, the undetectability that involves data imperceptibility or concealment and security is the significant trait of any steganography system. Presently, the design and development of an effective image steganography system are facing several challenges including low capacity, poor robustness and imperceptibility. To surmount such limitations, it is important to improve the capacity and security of the steganography system while maintaining a high signal-to-noise ratio (PSNR). Based on these factors, this study is aimed to design and develop a distinction grade value (DGV) method to effectively embed the secret data into a cover image for achieving a robust steganography scheme. The design and implementation of the proposed scheme involved three phases. First, a new encryption method called the shuffle the segments of secret message (SSSM) was incorporated with an enhanced Huffman compression algorithm to improve the text security and payload capacity of the scheme. Second, the Fibonacci-based image transformation decomposition method was used to extend the pixel's bit from 8 to 12 for improving the robustness of the scheme. Third, an improved embedding method was utilized by integrating a random block/pixel selection with the DGV and implicit secret key generation for enhancing the imperceptibility of the scheme. The performance of the proposed scheme was assessed experimentally to determine the imperceptibility, security, robustness and capacity. The standard USC-SIPI images dataset were used as the benchmarking for the performance evaluation and comparison of the proposed scheme with the previous works. The resistance of the proposed scheme was tested against the statistical, X2 , Histogram and non-structural steganalysis detection attacks. The obtained PSNR values revealed the accomplishment of higher imperceptibility and security by the proposed DGV scheme while a higher capacity compared to previous works. In short, the proposed steganography scheme outperformed the commercially available data hiding schemes, thereby resolved the existing issues

Steganography

Multi Layer Security (MLS) is the art of hiding the fact that communication is taking place, by hiding information in other information. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the internet. For hiding secret information in images, there exists a large variety of techniques some are more complex than others and all of them have respective strong and weak points. Different applications may require absolute invisibility of the secret information, while others require a large secret message to be hidden. This project report intends to give an overview of image encryption, its uses and techniques. It also attempts to identify the requirements of a good algorithm and briefly reflects on which techniques are more suitable for applications

Tamper detection of qur'anic text watermarking scheme based on vowel letters with Kashida using exclusive-or and queueing technique

The most sensitive Arabic text available online is the digital Holy Qur’an. This sacred Islamic religious book is recited by all Muslims worldwide including the non-Arabs as part of their worship needs. It should be protected from any kind of tampering to keep its invaluable meaning intact. Different characteristics of the Arabic letters like the vowels ( أ . و . ي ), Kashida (extended letters), and other symbols in the Holy Qur’an must be secured from alterations. The cover text of the al-Qur’an and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio (PSNR), Embedding Ratio (ER), and Normalized Cross-Correlation (NCC), thus the location for tamper detection gets low accuracy. Watermarking technique with enhanced attributes must therefore be designed for the Qur’an text using Arabic vowel letters with Kashida. Most of the existing detection methods that tried to achieve accurate results related to the tampered Qur’an text often show various limitations like diacritics, alif mad surah, double space, separate shapes of Arabic letters, and Kashida. The gap addressed by this research is to improve the security of Arabic text in the Holy Qur’an by using vowel letters with Kashida. The purpose of this research is to enhance Quran text watermarking scheme based on exclusive-or and reversing with queueing techniques. The methodology consists of four phases. The first phase is pre-processing followed by the embedding process phase to hide the data after the vowel letters wherein if the secret bit is ‘1’, insert the Kashida but do not insert it if the bit is ‘0’. The third phase is extraction process and the last phase is to evaluate the performance of the proposed scheme by using PSNR (for the imperceptibility), ER (for the capacity), and NCC (for the security of the watermarking). The experimental results revealed the improvement of the NCC by 1.77 %, PSNR by 9.6 %, and ER by 8.6 % compared to available current schemes. Hence, it can be concluded that the proposed scheme has the ability to detect the location of tampering accurately for attacks of insertion, deletion, and reordering

Bit inverting map method for improved steganography scheme

Achieving an efficient and accurate steganography scheme for hiding information is the foremost priority in the information and communication technology era. The developed scheme of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography scheme is the main issue to be addressed. This study proposes an improved Bit Inverting Map (BIM) method and a new scheme for embedding secret message into an image. This newly developed scheme is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select pixels before random embedding to select block of (64 64) pixels, followed by the Knight Tour algorithm to select sub-block of (8 8) pixels, and finally by the random pixels selection. The proposed BIM is distributed over the entire image to maintain high level of security against any kind of attack. One-bit indicator is used to decide if the secret bits are inserted directly or inversely, which enhanced the complexity of embedding process. Color and gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. Self-captured images are used to test the efficacy of the proposed BIM method. The results show good PSNR values of 72.9 and these findings verified the worthiness of the proposed BIM method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing scheme in the literature

Triple scheme based on image steganography to improve imperceptibility and security

A foremost priority in the information technology and communication era is achieving an effective and secure steganography scheme when considering information hiding. Commonly, the digital images are used as the cover for the steganography owing to their redundancy in the representation, making them hidden to the intruders. Nevertheless, any steganography system launched over the internet can be attacked upon recognizing the stego cover. Presently, the design and development of an effective image steganography system are facing several challenging issues including the low capacity, poor security, and imperceptibility. Towards overcoming the aforementioned issues, a new decomposition scheme was proposed for image steganography with a new approach known as a Triple Number Approach (TNA). In this study, three main stages were used to achieve objectives and overcome the issues of image steganography, beginning with image and text preparation, followed by embedding and culminating in extraction. Finally, the evaluation stage employed several evaluations in order to benchmark the results. Different contributions were presented with this study. The first contribution was a Triple Text Coding Method (TTCM), which was related to the preparation of secret messages prior to the embedding process. The second contribution was a Triple Embedding Method (TEM), which was related to the embedding process. The third contribution was related to security criteria which were based on a new partitioning of an image known as the Image Partitioning Method (IPM). The IPM proposed a random pixel selection, based on image partitioning into three phases with three iterations of the Hénon Map function. An enhanced Huffman coding algorithm was utilized to compress the secret message before TTCM process. A standard dataset from the Signal and Image Processing Institute (SIPI) containing color and grayscale images with 512 x 512 pixels were utilised in this study. Different parameters were used to test the performance of the proposed scheme based on security and imperceptibility (image quality). In image quality, four important measurements that were used are Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Square Error (MSE) and Histogram analysis. Whereas, two security measurements that were used are Human Visual System (HVS) and Chi-square (X2) attacks. In terms of PSNR and SSIM, the Lena grayscale image obtained results were 78.09 and 1 dB, respectively. Meanwhile, the HVS and X2 attacks obtained high results when compared to the existing scheme in the literature. Based on the findings, the proposed scheme give evidence to increase capacity, imperceptibility, and security to overcome existing issues

SInCom 2015

2nd Baden-Württemberg Center of Applied Research Symposium on Information and Communication Systems, SInCom 2015, 13. November 2015 in Konstan

Prediction of delamination in glass fibre reinforced composite materials using elasto-plastic modelling

Glass Fibre reinforced composite (GFRC) has been used for numerous structural applications in Aerospace, Chemical, Automotive and Civil infrastructure fields over a hundred of years. Due to this reason, understanding the intricate fracture behaviour of GFRC materials is crucial and essential for designing critical structural components. Voids and micro-cracks are considered as imperfections in Glass Fibre Reinforced composites. Much research has been undertaken on approaches to calculate and evaluate the effects of the imperfections on mechanical properties. However, it is an established fact that the micro-mechanical approach alone is not sufficient to understand a complete damage accumulation process during delamination. The damage mechanism which largely affects the performance of GFRC structures is commonly known as 'delamination'. Since the delamination is invisible, and hard to detect with ordinary non-destructive evaluation methods, therefore it is considered as a hidden killer which can cause catastrophic failure without any prior warnings. Due to this reason, research work on delamination modelling, damage detection and self-healing materials have been the highly placed research topics for more than five decades. Unfortunately there are a number of unresolved problems in delamination damage modelling and prediction, and few grey areas regarding application of Structural Health Monitoring systems to monitor delamination damages. This thesis has proposed to study the insight into the cause of delamination damage and its propagation mechanisms, by analytical modelling and experimental verifications. Within this research project, extension of the work by Tsukrov and Kachanov (2000) – “An innovative Elasto-plastic model” has been undertaken to evaluate, investigate and model the onset and propagation of delamination damages. Mode I, Mode II as well as Mixed Mode I/II delamination damage analysis has been utilised to study the proposed model predictions for GFRC structures for both in-plane and out-of-plane load applications. The proposed model has been validated using the Double Cantilever Beam (DCB), End Notch Flexure configurations (ENF) and Cracked Lap Shear (CLS) experiments on 0/90-glass woven cloth specimens. For the validation process, the procedures stipulated by ASTM standards were employed. It was observed that there were significant discrepancies between calculated fracture energies using standard procedures and the proposed model. Interestingly these observations have revealed some inconsistencies associated with the standard method for strain measurements that majorly controls the fracture energy calculations. This research project has demonstrated and evidently proven the accuracy of the proposed model predictions using the strain measured with embedded Fibre Bragg Grating (FBG) sensors, located inside the sample in proximity of the crack tip. The extended use of FBG strain measurement has created a breakthrough in Structural Health Monitoring (SHM) of composite structures. Non-availability of a suitable damage prediction model is an issue for accurate damage monitoring process. The proposed model has also demonstrated the potential for its integration with Structural Health Monitoring (SHM) systems. Additionally, Thermoplastic Stress Analysis (TSA) has been employed to monitor delamination. The potential for integration of FBG sensors and TSA techniques has been experimentally demonstrated during this project and, it is another breakthrough in SHM field as a result of this research. In addition to analytical model, a detailed Finite Element model was also created on ABAQUS commercial software. The cohesive elements with state variables (SDV) and UMAT codes were used for FEA simulations. Interestingly, the FEA results have shown an excellent correlation with the experimental results. Finally, this thesis has evidently proved the validity of the proposed model and integration of model with SHM system based on FBG sensors and TSA techniques. The outcomes of the thesis have provided a novel and innovative damage prediction model and a breakthrough technology for SHM systems