Digital steganalysis techniques attempt to detect hidden information in digital media. The rising interest in steganalysis is attributed to the growing number of steganography algorithms and the threats they represent. This article presents a combined maximum entropy energy approach for audio steganalysis. First, the audio signal is divided into four energy-based regions: noise, low, medium and...

The aim of the steganography methods is to communicate securely in a completely undetectable manner. LSB Matching and LSB Matching Revisited steganography methods are two general and esiest methods to achieve this aim. Being secured against first order steganalysis methods is the most important feature of these methods. On the other hand, these methods don't consider inter pixel dependency. The...

The main goals of this paper are to show the impact of the basic assumptions for the cover channel characteristics as well as the impact of different training/testing set generation strategies on the statistical detectability of exemplary chosen audio hiding approaches known from steganography and watermarking. Here we have selected exemplary five steganography algorithms and four watermarking ...

In this paper we present a new accurate steganalysis method for the LSB replacement steganography. The suggested method is based on the changes that occur in the histogram of an image after the embedding of data. Every pair of neighboring bins of a histogram are either inter-related or unrelated depending on whether embedding of a bit of data in the image could affect both bins or not. We show ...

Steganography is the art of secret communication between two parties that not only conceals the contents of a message, but also its existence. Steganalysis attempts to detect the existence of embedded data in a steganographically altered cover file. Many algorithms have been proposed, but so far each has had some weakness that has allowed its effects to be detected, usually through first or sec...

The proliferation of multimedia and the advent of the Internet and other public networks have created many new applications of information hiding in multimedia security and forensics. This dissertation focuses on two of these application scenarios: steganography (and its counter problem, steganalysis), and fingerprinting. First, from a detection-theoretic perspective, we quantify the detectabil...

Steganalysis of least significant bit (LSB) embedded images in spatial domain has been investigated extensively over the past decade and most well-known LSB steganography methods have been shown to be detectable. However, according to the latest findings in the area, two major issues of very low-rate (VLR) embedding and content-adaptive steganography have remained hard to resolve. The problem o...

Conventional steganalysis aims to separate cover objects from stego objects, working on each object individually. In this paper we investigate some methods for pooling steganalysis evidence, so as to obtain more reliable detection of steganography in large sets of objects, and the dual problem of hiding information securely when spreading across a batch of covers. The results are rather surpris...

Targeted steganalysis aims at detecting hidden data embedded by a particular algorithm without any knowledge of the ‘cover’ image. In this paper we propose a novel approach for detecting Perturbed Quantization Steganography (PQ) by HFS (Huffman FR index Steganalysis) algorithm using a combination of Huffman Bit Code Length (HBCL) Statistics and File size to Resolution ratio (FR Index) which is ...

We propose a new paradigm for blind, universal, steganalysis in the case when multiple actors transmit multiple objects, with guilty actors including some stego objects in their transmissions. The method is based on clustering rather than classification, and it is the actors which are clustered rather than their individual transmitted objects. This removes the need for training a classifier, an...