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

Designing Secure and Survivable Stegosystems

Steganography, the art and science of carrying out hidden communication, is an emergingsub-discipline of information security. Unlike cryptography, steganography conceals the existenceof a secret message by embedding it in an innocuous container digital media, thereby enablingunobstrusive communication over insecure channels. Detection and extraction of steganographiccontents is another challenge for the information security professional and this activity iscommonly known as steganalysis. Recent progress in steganalysis has posed a challenge fordesign and development of stegosystems with high levels of security and survivability. In thispaper, different strategies have been presented that can be used to escape detection and foilan eavesdropper having high technical capabilities as well as adequate infrastructure. Based onthe strength and weaknesses of current steganographic schemes, ideas have been progressedto make detection and destruction of hidden information more difficult

Analysis of MHPDM algorithm for data hiding in JPEG images

In the recent years, there has been a great deal of interest in developing a secure algorithm for hiding information in images, or steganography. There has also been a lot of research in steganalysis of images, which deals with the detection of hidden information in supposedly natural images. The first section of this thesis reviews the steganography algorithms and steganalysis techniques developed in the last few years. It discusses the breadth of steganographic algorithms and steganalytic techniques, starting with the earliest, based on LSB flipping of the DCT coefficients, to more recent and sophisticated algorithms for data hiding and equally clever steganalytic techniques. The next section focuses on the steganographic algorithm, MHPDM which was first developed by Eggers and then modified by Tzschoppe, Bauml, Huber and Kaup. The MHPDM algorithm preserves the histogram of the stego image and is thus perfectly secure in terms of Cachin\u27s security definition. The MHPDM algorithm is explained in detail and implemented in MATLAB. It is then tested on numerous images and steganalysed using Dr. Fridrich\u27s recent feature-based steganalytic technique. The thesis concludes with observations about the detectibility of MHPDM using feature-based steganalysis for different payloads (embedded message lengths)

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