Enhancing the Security and Quality Image Steganography using Hiding Algorithm based on Minimizing the Distortion

In this paper, highest state-of-the-art binary image Steganographic approach considers the spinning misinterpretation according to the personal visual structure, which will be not secure when they are attacked by Steganalyzers. In this paper, a binary image Steganographic scheme that aims to reduce the hiding misinterpretation on the balance is presented. We excerpt the complement, turn, and following-invariant local balance arrangement from the binary image first. The weighted sum of Complement, Turn, And Following-Invariant Local Balance changes when spinning one pixel is then employed to allot the spinning misinterpretation corresponding to that pixel. By examining on both simple binary images and the composed image constructed message set, we show that the advanced appraisal can well describe the misinterpretations on both visual aspect and statistics. Based on the proposed measurement, a practical Steganographic scheme is develope

Universal Image Steganalytic Method

In the paper we introduce a new universal steganalytic method in JPEG file format that is detecting well-known and also newly developed steganographic methods. The steganalytic model is trained by MHF-DZ steganographic algorithm previously designed by the same authors. The calibration technique with the Feature Based Steganalysis (FBS) was employed in order to identify statistical changes caused by embedding a secret data into original image. The steganalyzer concept utilizes Support Vector Machine (SVM) classification for training a model that is later used by the same steganalyzer in order to identify between a clean (cover) and steganographic image. The aim of the paper was to analyze the variety in accuracy of detection results (ACR) while detecting testing steganographic algorithms as F5, Outguess, Model Based Steganography without deblocking, JP Hide&Seek which represent the generally used steganographic tools. The comparison of four feature vectors with different lengths FBS (22), FBS (66) FBS(274) and FBS(285) shows promising results of proposed universal steganalytic method comparing to binary methods

Perfectly secure steganography: hiding information in the quantum noise of a photograph

We show that the quantum nature of light can be used to hide a secret message within a photograph. Using this physical principle we achieve information-theoretic secure steganography, which had remained elusive until now. The protocol is such that the digital picture in which the secret message is embedded is perfectly undistinguishable from an ordinary photograph. This implies that, on a fundamental level, it is impossible to discriminate a private communication from an exchange of photographs.Comment: 5 pages, 3 figures + appendix : 5 pages, 6 figure

Steganographic Generative Adversarial Networks

Steganography is collection of methods to hide secret information ("payload") within non-secret information "container"). Its counterpart, Steganalysis, is the practice of determining if a message contains a hidden payload, and recovering it if possible. Presence of hidden payloads is typically detected by a binary classifier. In the present study, we propose a new model for generating image-like containers based on Deep Convolutional Generative Adversarial Networks (DCGAN). This approach allows to generate more setganalysis-secure message embedding using standard steganography algorithms. Experiment results demonstrate that the new model successfully deceives the steganography analyzer, and for this reason, can be used in steganographic applications.Comment: 15 pages, 10 figures, 5 tables, Workshop on Adversarial Training (NIPS 2016, Barcelona, Spain