Generalized PVO‐based dynamic block reversible data hiding for secure transmission using firefly algorithm

In this paper, we proposed a novel generalized pixel value ordering–based reversible data hiding using firefly algorithm (GPVOFA). The sequence of minimum and maximum number pixels value has been used to embed the secret data while prediction and modification are held on minimum, and the maximum number of pixel blocks is used to embed the secret data into multiple bits. The host image is divided into the size of noncoinciding dynamic blocks on the basis of firefly quadtree partition, whereas rough blocks are divided into a larger size; moreover, providing more embedding capacity used small flat blocks size and optimal location in the block to write the information. Our proposed method becomes able to embed large data into a host image with low distortion. The rich experimental results are better, as compared with related preceding arts

A New Reversible Data Hiding Scheme Based on Efficient Prediction

This paper presents a new reversible data hiding scheme based on a popular technique, namely prediction error expansion (PEE). The prediction accuracy is important to the efficiency of this kind of scheme. We predict the pixels through their six round neighboring ones. And the gradient information is also taken into consideration. As a result the proposed prediction method helps us to obtain a large data hiding space. Furthermore, a sorting strategy that tries to reduce the overflow/underflow problems is employed to improve the algorithm efficiency. Experimental results prove that the proposed reversible data hiding scheme outperforms the most prior arts. ? 2014 Springer-Verlag Berlin Heidelberg.EI

Reversible data hiding in encrypted images based on image partition and spatial correlation

Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images because of its better protection of privacy compared with traditional RDH methods directly operated in original images. In several RDH algorithms, prediction-error expansion (PEE) is proved to be superior to other methods in terms of embedding capacity and distortion of marked image and multiple histograms modification (MHM) can realize adaptive selection of expansion bins which depends on image content in the modification of a sequence of histograms. Therefore, in this paper, we propose an efficient RDH method in encrypted images by combining PEE and MHM, and design corresponding mode of image partition. We first divide the image into three parts: W (for embedding secret data), B (for embedding the least significant bit(LSB) of W) and G (for generating prediction-error histograms). Then, we apply PEE and MHM to embed the LSB of W to reserve space for secret data. Next, we encrypt the image and change the LSB of W to realize the embedding of secret data. In the process of extraction, the reversibility of image and secret data can be guaranteed. The utilization of correlation between neighbor pixels and embedded order decided by the smoothness of pixel in part W contribute to the performance of our method. Compared to the existing algorithms, experimental results show that the proposed method can reduce distortion to the image at given embedding capacity especially at low embedding capacity

Steganalysis to Data Hiding of VQ Watermarking Upon Grouping Strategy

Part 2: The 2014 Asian Conference on Availability, Reliability and Security, AsiaARES 2014International audienceThis paper present a steganalysis method for the data hiding scheme based on VQ-compression. This data hiding algorithm divides the codebook into groups which contain two codewords each. The Euclidean Distance of the group is used instead of a codeword in traditional VQ-compression. A PoV-like effect of Chi-square attack is observed and used as a feature of detection. In the proposed steganalysis, we detect whether an unknown image is a VQ-compressed image or not, and then the target detection of codewords grouping type data hiding methods is proposed. We apply proposed scheme to Yang et al.’s watermarking scheme. A large amount test image database UCID (Uncompressed Colour Image Database) is utilized as various conditions, such as cover imaged, traditional VQ-compressed images, and stego images. The experimental shows that the proposed steganalysis method is able to identify the stego images among others, and the accuracy rate reaches over 90 %