A dual watermarking scheme for identity protection

A novel dual watermarking scheme with potential applications in identity protection, media integrity maintenance and copyright protection in both electronic and printed media is presented. The proposed watermarking scheme uses the owner’s signature and fingerprint as watermarks through which the ownership and validity of the media can be proven and kept intact. To begin with, the proposed watermarking scheme is implemented on continuous-tone/greyscale images, and later extended to images achieved via multitoning, an advanced version of halftoning-based printing. The proposed watermark embedding is robust and imperceptible. Experimental simulations and evaluations of the proposed method show excellent results from both objective and subjective view-points

A novel multipurpose watermarking scheme capable of protecting and authenticating images with tamper detection and localisation abilities

Technologies that fall under the umbrella of Industry 4.0 can be classified into one of its four significant components: cyber-physical systems, the internet of things (IoT), on-demand availability of computer system resources, and cognitive computing. The success of this industrial revolution lies in how well these components can communicate with each other, and work together in finding the most optimised solution for an assigned task. It is achieved by sharing data collected from a network of sensors. This data is communicated via images, videos, and a variety of other signals, attracting unwanted attention of hackers. The protection of such data is therefore pivotal, as is maintaining its integrity. To this end, this paper proposes a novel image watermarking scheme with potential applications in Industry 4.0. The strategy presented is multipurpose; one such purpose is authenticating the transmitted image, another is curtailing the illegal distribution of the image by providing copyright protection. To this end, two new watermarking methods are introduced, one of which is for embedding the robust watermark, and the other is related to the fragile watermark. The robust watermark's embedding is achieved in the frequency domain, wherein the frequency coefficients are selected using a novel mean-based coefficient selection procedure. Subsequently, the selected coefficients are manipulated in equal proportion to embed the robust watermark. The fragile watermark's embedding is achieved in the spatial domain, wherein self-generated fragile watermark(s) is embedded by directly altering the pixel bits of the host image. The effective combination of two domains results in a hybrid scheme and attains the vital balance between the watermarking requirements of imperceptibility, security and capacity. Moreover, in the case of tampering, the proposed scheme not only authenticates and provides copyright protection to images but can also detect tampering and localise the tampered regions. An extensive evaluation of the proposed scheme on typical images has proven its superiority over existing state-of-the-art methods

Towards Deep Network Steganography: From Networks to Networks

With the widespread applications of the deep neural network (DNN), how to covertly transmit the DNN models in public channels brings us the attention, especially for those trained for secret-learning tasks. In this paper, we propose deep network steganography for the covert communication of DNN models. Unlike the existing steganography schemes which focus on the subtle modification of the cover data to accommodate the secrets, our scheme is learning task oriented, where the learning task of the secret DNN model (termed as secret-learning task) is disguised into another ordinary learning task conducted in a stego DNN model (termed as stego-learning task). To this end, we propose a gradient-based filter insertion scheme to insert interference filters into the important positions in the secret DNN model to form a stego DNN model. These positions are then embedded into the stego DNN model using a key by side information hiding. Finally, we activate the interference filters by a partial optimization strategy, such that the generated stego DNN model works on the stego-learning task. We conduct the experiments on both the intra-task steganography and inter-task steganography (i.e., the secret and stego-learning tasks belong to the same and different categories), both of which demonstrate the effectiveness of our proposed method for covert communication of DNN models.Comment: 8 pages. arXiv admin note: text overlap with arXiv:2302.1452

A single watermark based scheme for both protection and authentication of identities

The security of a watermarking scheme is mainly categorised as either robust or fragile. The former can withstand an authorised alteration/attack, primarily used in copyright protection. The latter follows a zero tolerance towards any modification, used primarily in content authentication processes. The existing literature in the field projects that two separate watermarks are required to make a watermarking scheme robust and fragile, thus making the overall process cumbersome and complex. A novel image watermarking scheme that uses only one watermark while achieving both goals of copyright protection and authentication of identities is presented. An unconventional concept of checkpointing is introduced, which equips the proposed scheme to be either robust or fragile, making it superior in its application versatility. First, watermark embedding within the host/original image is achieved by a combination of transform domain techniques along with a novel median-based embedding block selection procedure. Second, checkpointing is performed in the spatial domain. The watermarked image in the absence of an attack is correlated to the one that is being attacked, using the template energy comparison-based approach. In the case of the robust watermark, such checkpointing can establish whether the carried out attack is authorised or not, determining the successful recovery of the watermark or vice-versa. Moreover, in the case of the fragile watermark, a sole confirmation of the occurrence of an attack is sufficient to make the watermark recovery impossible. Finally, the experimental analysis of the proposed scheme illustrates its excellent performance and superiority over state-of-the-art methods within the field

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

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

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