Data Transfer through an Image and Its Recovery Causing Minimum Distortion in the Carrier Image: A Survey

This paper, tries to address the problem of transmitting the huge amount of data over a communication channel hidden into an image and making sure that there is minimum distortion created into the image carrying that secret data. In this project the sender or the data owner who wants to send his data first encrypts the data and then store that encrypted data in such an efficient way that it required minimum number of bits to be altered to hide the data into an Image. This efficiency is created using the LFSR algorithm which is applied on the secret key which in turn creates a unique set of keys which are checked and used for hiding the data. The data too is not hidden sequentially into an image, it is hidden randomly based on the secret key making it more complicated. Once the data is hidden the image the, it is encrypted using the AES algorithm. Here too it adds the encryption in parallel where the image is divided into equal parts and then the AES algorithm is applied to all the parts of the image simultaneously, thus saving our time in the encryption process. Thus shows a significant time saving in case the large images are used. This image when encrypted is send to the receiver and at the receivers end ,the one who has the correct keys can only get back the original image and the secret data. This makes sure that the receiver get the correct data and the image with minimum distortion

High Capacity Reversible Data Hiding for Encrypted 3D Mesh Models Based on Topology

Reversible data hiding in encrypted domain(RDH-ED) can not only protect the privacy of 3D mesh models and embed additional data, but also recover original models and extract additional data losslessly. However, due to the insufficient use of model topology, the existing methods have not achieved satisfactory results in terms of embedding capacity. To further improve the capacity, a RDH-ED method is proposed based on the topology of the 3D mesh models, which divides the vertices into two parts: embedding set and prediction set. And after integer mapping, the embedding ability of the embedding set is calculated by the prediction set. It is then passed to the data hider for embedding additional data. Finally, the additional data and the original models can be extracted and recovered respectively by the receiver with the correct keys. Experiments declare that compared with the existing methods, this method can obtain the highest embedding capacity

An Efficient MSB Prediction-Based Method for High-Capacity Reversible Data Hiding in Encrypted Images

International audienceReversible data hiding in encrypted images (RDHEI) is an effective technique to embed data in the encrypted domain. An original image is encrypted with a secret key and during or after its transmission, it is possible to embed additional information in the encrypted image, without knowing the encryp-tion key or the original content of the image. During the decoding process, the secret message can be extracted and the original image can be reconstructed. In the last few years, RDHEI has started to draw research interest. Indeed, with the development of cloud computing, data privacy has become a real issue. However, none of the existing methods allow us to hide a large amount of information in a reversible manner. In this paper, we propose a new reversible method based on MSB (most significant bit) prediction with a very high capacity. We present two approaches, these are: high capacity reversible data hiding approach with correction of prediction errors and high capacity reversible data hiding approach with embedded prediction errors. With this method, regardless of the approach used, our results are better than those obtained with current state of the art methods, both in terms of reconstructed image quality and embedding capacity

An Efficient Data Security System Using Reserve Room Approach on Digital Images for Secret Sharing

This paper presents enhancement of d ata protection system for secret communication through common network based on reversible data concealment in encrypted images with reserve room approach. In this paper was implemented for true color RGB image and reserve room approach under multi scale decomposition. The Blue plane will be chosen for hiding the secret text data. Then image is then separated into number of blocks locally and lifting wavelet will be used to detect approximation and detailed coefficients. Then approximation part is encrypted using chaos encryption method. The proposed encryption technique uses the key to encrypt an image and not only enhances the safety of secret carrier informa tion by making the information inaccessible to any intruder having a random method. After image encryption, the data hide r will conceal the secret data into the detailed coefficients which are reserved before encryption. Although encryption achieves certain security effects, they make the secret messages unreadable and unnatural or meaningless. This system is still enhanced with encrypt messages using a symmetric key method. This is the reason a new security approach called reversible data hiding arises. It is the art of hiding the existence of data in another transmission medium to achieve secret communication. The data hidi ng technique uses the adaptive LSB replacement algorithm for concealing the secret message bits into the encrypted image. In the data extraction module, the secret data will be extracted by using relevant key for choosing the encrypted pixe ls to extract th e data. By using the decryption keys, the image and extracted text data will be extracted from encryption to get the original informatio n. Finally the performance of this proposal in encryption and data hiding will be analyzed based on image and data recovery

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