Data Security using Reversible Data Hiding with Optimal Value Transfer

In this paper a novel reversible data hiding algorithm is used which can recover image without any distortion. This algorithm uses zero or minimum points of an image and modifies the pixel. It is proved experimentally that the peak signal to noise ratio of the marked image generated by this method and the original image is guaranteed to be above 48 dB this lower bound of peak signal to noise ratio is much higher than all reversible data hiding technique present in the literature. Execution time of proposed system is short. The algorithm has been successfully applied to all types of images

Reversible data hiding in JPEG images based on adjustable padding

In this paper, we propose a reversible data hiding scheme that enables an adjustable amount of information to be embedded in JPEG images based on padding strategy. The proposed embedding algorithm only modifies, in a subtle manner, an adjustable number of zero-valued quantised DCT coefficients to embed the message. Hence, compared with a state-of-the-art based on histogram shifting, the proposed scheme has a relatively low distortion to the host images. In addition to this, we found that by representing the message in ternary instead of in binary, we can embed a greater amount of information while the level of distortion remains unchanged. Experimental results support that the proposed scheme can achieve better visual quality of the marked JPEG image than the histogram shifting based scheme. The proposed scheme also outperforms this state-of-the-art in terms of the ease of implementation

A Framework to Reversible Data Hiding Using Histogram-Modification

A Novel method of Stegnography to achieve Reversible Data Hiding (RDH) is proposed using Histogram Modification (HM). In this paper the HM technique is revisited and a general framework to construct HM-based RDH is presented by simply designing the shifting and embedding functions on the cover image. The Secret Image is embedded inside the cover image using several steps of specific shifting of pixels with an order. The secret image or logo is retrieved without any loss in data on the cover and as well as in the secrete image. The Experimental results show the better Peak Signal to Noise Ratio (PSNR) with the existing methods

A Brief Review of RIDH

The Reversible image data hiding (RIDH) is one of the novel approaches in the security field. In the highly sensitive domains like Medical, Military, Research labs, it is important to recover the cover image successfully, Hence, without applying the normal steganography, we can use RIDH to get the better result. Reversible data hiding has a advantage over image data hiding that it can give you double security surely

Vector-based Efficient Data Hiding in Encrypted Images via Multi-MSB Replacement

As an essential technique for data privacy protection, reversible data hiding in encrypted images (RDHEI) methods have drawn intensive research interest in recent years. In response to the increasing demand for protecting data privacy, novel methods that perform RDHEI are continually being developed. We propose two effective multi-MSB (most significant bit) replacement-based approaches that yield comparably high data embedding capacity, improve overall processing speed, and enhance reconstructed images' quality. Our first method, Efficient Multi-MSB Replacement-RDHEI (EMR-RDHEI), obtains higher data embedding rates (DERs, also known as payloads) and better visual quality in reconstructed images when compared with many other state-of-the-art methods. Our second method, Lossless Multi-MSB Replacement-RDHEI (LMR-RDHEI), can losslessly recover original images after an information embedding process is performed. To verify the accuracy of our methods, we compared them with other recent RDHEI techniques and performed extensive experiments using the widely accepted BOWS-2 dataset. Our experimental results showed that the DER of our EMR-RDHEI method ranged from 1.2087 bit per pixel (bpp) to 6.2682 bpp with an average of 3.2457 bpp. For the LMR-RDHEI method, the average DER was 2.5325 bpp, with a range between 0.2129 bpp and 6.0168 bpp. Our results demonstrate that these methods outperform many other state-of-the-art RDHEI algorithms. Additionally, the multi-MSB replacement-based approach provides a clean design and efficient vectorized implementation.Comment: 14 pages; journa

An Enhanced Reversible Data Hiding Technique for Coloured Images

To maintain image contents confidentiality and to recover original image, there is a need of Reversible Data Hiding scheme. This paper proposes an enhanced reversible data hiding technique for the coloured image. All previous methods embed data by reversibly vacating room from the encrypted images, which may be subject to some errors on data extraction or image restoration. The proposed method embeds data by reserving room before encryption with a traditional RDH algorithm. It is easy for the data hider to reversibly embed data in the encrypted image. This paper also concerns with a method that embeds the data invisibly into an image. The transmission and exchange of image also needs a high security. To achieve a security, Visual Cryptography is used. Visual cryptography maintains security of a cover media and also it will not make a use of encryption key. Hence, it is less prone to attack. The proposed method can achieve real reversibility, that is, data extraction and image recovery are free of any error

Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

This work presents an intelligent technique based on reversible watermarking for protecting patient and medical related information. In the proposed technique ‘IRW-Med’, the concept of companding function is exploited for reducing embedding distortion, while Integer Wavelet Transform (IWT) is used as an embedding domain for achieving reversibility. Histogram processing is employed to avoid underflow/overflow. In addition, the learning capabilities of Genetic Programming (GP) are exploited for intelligent wavelet coefficient selection. In this context, GP is used to evolve models that not only make an optimal tradeoff between imperceptibility and capacity of the watermark, but also exploit the wavelet coefficient hidden dependencies and information related to the type of sub band. The novelty of the proposed IRW-Med technique lies in its ability to generate a model that can find optimal wavelet coefficients for embedding, and also acts as a companding factor for watermark embedding. The proposed IRW-Med is thus able to embed watermark with low distortion, take out the hidden information, and also recovers the original image. The proposed IRW-Med technique is effective with respect to capacity and imperceptibility and effectiveness is demonstrated through experimental comparisons with existing techniques using standard images as well as a publically available medical image dataset