Pixel grouping of digital images for reversible data hiding

Pixel Grouping (PG) of digital images has been a key consideration in recent development of the Reversible Data Hiding (RDH) schemes. While a PG kernel with neighborhood pixels helps compute image groups for better embedding rate-distortion performance, only horizontal neighborhood pixel group of size 1×3 has so far been considered. In this paper, we formulate PG kernels of sizes 3×1, 2×3 and 3×2 and investigate their effect on the rate-distortion performance of a prominent PG-based RDH scheme. Specially, a kernel of size 3×2 (or 2×3) that creates a pair of pixel-trios having triangular shape and offers a greater possible correlation among the pixels. This kernel thus can be better utilized for improving a PG-based RDH scheme. Considering this, we develop and present an improved PG-based RDH scheme and the computational models of its key processes. Experimental results demonstrated that our proposed RDH scheme offers reasonably better  embedding rate-distortion performance than the original scheme

Enhancement Of Pixel Value Ordering Based Data Hiding By Row Block Partition

The development of information and communication technology that support digital data transmission such as text, image, audio and video gives several effects. One of them is data security that becomes the main priority during the transmission process. Pixel-Value-Ordering (PVO) which one of data hiding methods can be implemented to achieve the requirement. It embeds data on maximum pixel and minimum pixel in a blok which is a part of the carrier image. However, PVO has capacity a problem, that only 2 bits per block can be hidden. To handle this problem, we propose a new approach by dividing blocks dinamically based on its complexity. These blocks are grouped into 4: smooth block, semi-smooth block, normal block and rough block. Using this approach, the stego capacity can be improved up to 2.6 times in average of previous method by keeping the quality stego more than 65 dB for all testing image

Reversible Data Hiding scheme using modified Histogram Shifting in Encrypted Images for Bio-medical images

Existing Least Significant Bit (LSB) steganography system is less robust and the stego-images can be corrupted easily by attackers. To overcome these problems Reversible data hiding (RDH) techniques are used. RDH is an efficient way of embedding confidential message into a cover image. Histogram expansion and histogram shifting are effective techniques in reversible data hiding. The embedded message and cover images can be extracted without any distortion. The proposed system focuses on implementation of RDH techniques for hiding data in encrypted bio-medical images without any loss. In the proposed techniques the bio-medical data are embedded into cover images by reversible data hiding technique. Histogram expansion and histogram shifting have been used to extract cover image and bio- medical data. Each pixel is encrypted by public key of Paillier cryptosystem algorithm. The homomorphic multiplication is used to expand the histogram of the image in encrypted domain. The histogram shifting is done based on the homomorphic addition and adjacent pixel difference in the encrypted domain. The message is embedded into the host image pixel difference. On receiving encrypted image with additional data, the receiver using his private key performs decryption. As a result, due to histogram expansion and histogram shifting embedded message and the host image can be recovered perfectly. The embedding rate is increased in host image than in existing scheme due to adjacency pixel difference

ENHANCEMENT OF PIXEL VALUE ORDERING BASED DATA HIDING BY ROW BLOCK PARTITION

The development of information and communication technology that support digital data transmission such as text, image, audio and video gives several effects. One of them is data security that becomes the main priority during the transmission process. Pixel-Value-Ordering (PVO) which one of data hiding methods can be implemented to achieve the requirement. It embeds data on maximum pixel and minimum pixel in a blok which is a part of the carrier image. However, PVO has capacity a problem, that only 2 bits per block can be hidden. To handle this problem, we propose a new approach by dividing blocks dinamically based on its complexity. These blocks are grouped into 4: smooth block, semi-smooth block, normal block and rough block. Using this approach, the stego capacity can be improved up to 2.6 times in average of  previous method by keeping the quality stego more than 65 dB for all testing image

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

Reversible Data Hiding scheme using modified Histogram Shifting in Encrypted Images for Bio-medical images

Existing Least Significant Bit (LSB) steganography system is less robust and the stego-images can be corrupted easily by attackers. To overcome these problems Reversible data hiding (RDH) techniques are used. RDH is an efficient way of embedding confidential message into a cover image. Histogram expansion and histogram shifting are effective techniques in reversible data hiding. The embedded message and cover images can be extracted without any distortion. The proposed system focuses on implementation of RDH techniques for hiding data in encrypted bio-medical images without any loss. In the proposed techniques the bio-medical data are embedded into cover images by reversible data hiding technique. Histogram expansion and histogram shifting have been used to extract cover image and bio- medical data. Each pixel is encrypted by public key of Paillier cryptosystem algorithm. The homomorphic multiplication is used to expand the histogram of the image in encrypted domain. The histogram shifting is done based on the homomorphic addition and adjacent pixel difference in the encrypted domain. The message is embedded into the host image pixel difference. On receiving encrypted image with additional data, the receiver using his private key performs decryption. As a result, due to histogram expansion and histogram shifting embedded message and the host image can be recovered perfectly. The embedding rate is increased in host image than in existing scheme due to adjacency pixel difference

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

Reversible Deep Neural Network Watermarking:Matching the Floating-point Weights

Static deep neural network (DNN) watermarking embeds watermarks into the weights of DNN model by irreversible methods, but this will cause permanent damage to watermarked model and can not meet the requirements of integrity authentication. For these reasons, reversible data hiding (RDH) seems more attractive for the copyright protection of DNNs. This paper proposes a novel RDH-based static DNN watermarking method by improving the non-reversible quantization index modulation (QIM). Targeting the floating-point weights of DNNs, the idea of our RDH method is to add a scaled quantization error back to the cover object. Two schemes are designed to realize the integrity protection and legitimate authentication of DNNs. Simulation results on training loss and classification accuracy justify the superior feasibility, effectiveness and adaptability of the proposed method over histogram shifting (HS).Comment: 21 page