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Detected Steganography Message Figure 9. No steganography message detected
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In recent years there has been a noticeable growth in the quantity of available Steganography tools on the World Wide Web. Steganography may be used to hide messages within images and it is widely believed that terrorist organizations may be communicating through the use of steganography. With this in mind there is a need to detect hidden data usin...
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The PHase-Aware pRojection Model (PHARM) feature set, built as phase-aware histograms of quantized projections obtained by convolving residuals with random matrices, achieves competitive detection performance against modern adaptive JPEG steganography while having significant computational cost. In this paper, we propose three improvements to the o...
Performance measurements which characterize digital image steganography techniques include payload capacity, stego image quality, and security (secret message detectability). Increasing payload capacity leads to diminishing both stego image quality and security. Conversely, a high stego image quality and a high security cannot be obtained without c...
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Citations
... Steganalysis has two main types of techniques: Statistical analysis and Visual analysis [24,25]. Visual analysis depends on human eyes. ...
... In visual analysis, human abilities are used to detect the presence of hidden information and secret communication. Visual inspection by eye can distinguish and succeed in detecting hidden messages, especially when secret information is embedded in the smooth area of an image [24,25]. ...
... Statistical analysis is usually used to detect steganography. It can identify tiny modifications in the statistical properties of the image caused by steganography [24,25]. ...
Embedding a message in media files, also known as steganography, is a common approach to hide secret information. It has been exploited by some criminals to confidentially exchange messages. As a countermeasure, tools have been developed in order to detect hidden information form digital media such as text, image, audio or video files. However the efficiency and performance of previous approaches still have room for improvement. In this research, we focus on algorithm design for better efficiency of hidden message detection from PNG files. We employ three classic AI approaches including neural network, fuzzy logic, and genetic algorithm and evaluate their efficiency and performance in controlled experiments. Finally we introduce our message detection system for PNG files based on LSB approach and present its usability in different case scenarios.
In 2014 it was estimated that 1.8 billion images were uploaded daily to the Internet, and in 2018 it is estimated that 3.2 billion images are shared daily. Some of these uploaded images may contain hidden information that can potentially be malicious (e.g. an image that contains hidden information regarding terrorism recruitment) or may cause serious damage (e.g. an employee wishing to hide sensitive company details in an image file and exporting the image to third parties). This research studied the most effective methods in manipulating images to hide information (Data Loss). Significant work has been done on computational algorithmic detection. Yet the desired output from this work was to find the point at which a human can no longer visually establish the difference between an original image and a manipulated image. This research examines the extent of use for file formats, bit depth alterations, least significant bits, message and audio concealment and watermark and filtering techniques for image steganography. The findings of this study indicated that audio insertion and picture insertion into cover image files are the strongest in deceiving the human eye. These results have been categorised for human visual perception in image-based steganography.
Steganography is the art of passing information in a manner that the very existence of the message is unknown. The goal of steganography is to avoid drawing suspicion to the transmission of a hidden message. If suspicion is raised, then this goal is defeated. In this paper a novel method for embedding messages in an image with increased capacity is proposed. Discrete Walsh Transform is used to increase the capacity of the cover image without any perceptible change in the stego image.
