JRevealPEG: A Semi-Blind JPEG Steganalysis Tool Targeting Current Open-Source Embedding Programs

Steganography in computer science refers to the hiding of messages or data within other messages or data; the detection of these hidden messages is called steganalysis. Digital steganography can be used to hide any type of file or data, including text, images, audio, and video inside other text, image, audio, or video data. While steganography can be used to legitimately hide data for non-malicious purposes, it is also frequently used in a malicious manner. This paper proposes JRevealPEG, a software tool written in Python that will aid in the detection of steganography in JPEG images with respect to identifying a targeted set of open-source embedding tools. It is hoped that JRevealPEG will assist in furthering the research into effective steganalysis techniques, to ultimately help identify the source of hidden and possibly sensitive or malicious messages, as well as contribute to efforts at thwarting the activities of bad actors

Steganography-based secret and reliable communications: Improving steganographic capacity and imperceptibility

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Unlike encryption, steganography hides the very existence of secret information rather than hiding its meaning only. Image based steganography is the most common system used since digital images are widely used over the Internet and Web. However, the capacity is mostly limited and restricted by the size of cover images. In addition, there is a tradeoff between both steganographic capacity and stego image quality. Therefore, increasing steganographic capacity and enhancing stego image quality are still challenges, and this is exactly our research main aim. Related to this, we also investigate hiding secret information in communication protocols, namely Simple Object Access Protocol (SOAP) message, rather than in conventional digital files. To get a high steganographic capacity, two novel steganography methods were proposed. The first method was based on using 16x16 non-overlapping blocks and quantisation table for Joint Photographic Experts Group (JPEG) compression instead of 8x8. Then, the quality of JPEG stego images was enhanced by using optimised quantisation tables instead of the default tables. The second method, the hybrid method, was based on using optimised quantisation tables and two hiding techniques: JSteg along with our first proposed method. To increase the steganographic capacity, the impact of hiding data within image chrominance was investigated and explained. Since peak signal-to-noise ratio (PSNR) is extensively used as a quality measure of stego images, the reliability of PSNR for stego images was also evaluated in the work described in this thesis. Finally, to eliminate any detectable traces that traditional steganography may leave in stego files, a novel and undetectable steganography method based on SOAP messages was proposed. All methods proposed have been empirically validated as to indicate their utility and value. The results revealed that our methods and suggestions improved the main aspects of image steganography. Nevertheless, PSNR was found not to be a reliable quality evaluation measure to be used with stego image. On the other hand, information hiding in SOAP messages represented a distinctive way for undetectable and secret communication.The Ministry of Higher Education in Syria and the University of Alepp

Theoretical model of the FLD ensemble classifier based on hypothesis testing theory

International audienceThe FLD ensemble classifier is a widely used machine learning tool for steganalysis of digital media due to its efficiency when working with high dimensional feature sets. This paper explains how this classifier can be formulated within the framework of optimal detection by using an accurate statistical model of base learners' projections and the hypothesis testing theory. A substantial advantage of this formulation is the ability to theoretically establish the test properties, including the probability of false alarm and the test power, and the flexibility to use other criteria of optimality than the conventional total probability of error. Numerical results on real images show the sharpness of the theoretically established results and the relevance of the proposed methodology

Pokročilé metody detekce steganografického obsahu

Steganography can be used for illegal activities. It is essential to be prepared. To detect steganography images, we have a counter-technique known as steganalysis. There are different steganalysis types, depending on if the original artifact (cover work) is known or not, or we know which algorithm was used for embedding. In terms of practical use, the most important are “blind steganalysis” methods that can be applied to image files because we do not have the original cover work for comparison. This philosophiæ doctor thesis describes the methodology to the issues of image steganalysis.In this work, it is crucial to understand the behavior of the targeted steganography algorithm. Then we can use it is weaknesses to increase the detection capability and success of categorization. We are primarily focusing on breaking the steganography algorithm OutGuess2.0. and secondary on breaking the F5 algorithm. We are analyzing the detector's ability, which utilizes a calibration process, blockiness calculation, and shallow neural network, to detect the presence of steganography message in the suspected image. The new approach and results are discussed in this Ph.D. thesis.Steganografie může být využita k nelegálním aktivitám. Proto je velmi důležité být připraven. K detekci steganografického obrázku máme k dispozici techniku známou jako stegoanalýza. Existují různé typy stegoanalýzy v závislosti na tom, zda je znám originální nosič nebo zdali víme, jaký byl použit algoritmus pro vložení tajné zprávy. Z hlediska praktického použití jsou nejdůležitější metody "slepé stagoanalýzy", které zle aplikovat na obrazové soubory a jelikož nemáme originální nosič pro srovnání. Tato doktorská práce popisuje metodologii obrazové stegoanalýzy. V této práci je důležité porozumět chování cíleného steganografického algoritmu. Pak můžeme využít jeho slabiny ke zvýšení detekční schopnosti a úspěšnosti kategorizace. Primárně se zaměřujeme na prolomení steganografického algoritmu OutGuess2.0 a sekundárně na algoritmus F5. Analyzujeme schopnost detektoru, který využívá proces kalibrace, výpočtu shlukování a mělkou neuronovou síť k detekci přítomnosti steganografické zprávy na podezřelém snímku. Nový přístup a výsledky jsou sepsány v této doktorské práci.460 - Katedra informatikyvyhově

Steganography-based secret and reliable communications : improving steganographic capacity and imperceptibility

Unlike encryption, steganography hides the very existence of secret information rather than hiding its meaning only. Image based steganography is the most common system used since digital images are widely used over the Internet and Web. However, the capacity is mostly limited and restricted by the size of cover images. In addition, there is a tradeoff between both steganographic capacity and stego image quality. Therefore, increasing steganographic capacity and enhancing stego image quality are still challenges, and this is exactly our research main aim. Related to this, we also investigate hiding secret information in communication protocols, namely Simple Object Access Protocol (SOAP) message, rather than in conventional digital files. To get a high steganographic capacity, two novel steganography methods were proposed. The first method was based on using 16x16 non-overlapping blocks and quantisation table for Joint Photographic Experts Group (JPEG) compression instead of 8x8. Then, the quality of JPEG stego images was enhanced by using optimised quantisation tables instead of the default tables. The second method, the hybrid method, was based on using optimised quantisation tables and two hiding techniques: JSteg along with our first proposed method. To increase the steganographic capacity, the impact of hiding data within image chrominance was investigated and explained. Since peak signal-to-noise ratio (PSNR) is extensively used as a quality measure of stego images, the reliability of PSNR for stego images was also evaluated in the work described in this thesis. Finally, to eliminate any detectable traces that traditional steganography may leave in stego files, a novel and undetectable steganography method based on SOAP messages was proposed. All methods proposed have been empirically validated as to indicate their utility and value. The results revealed that our methods and suggestions improved the main aspects of image steganography. Nevertheless, PSNR was found not to be a reliable quality evaluation measure to be used with stego image. On the other hand, information hiding in SOAP messages represented a distinctive way for undetectable and secret communication.EThOS - Electronic Theses Online ServiceMinistry of Higher Education in SyriaUniversity of AleppoGBUnited Kingdo

Steganography-based secret and reliable communications : improving steganographic capacity and imperceptibility

Unlike encryption, steganography hides the very existence of secret information rather than hiding its meaning only. Image based steganography is the most common system used since digital images are widely used over the Internet and Web. However, the capacity is mostly limited and restricted by the size of cover images. In addition, there is a tradeoff between both steganographic capacity and stego image quality. Therefore, increasing steganographic capacity and enhancing stego image quality are still challenges, and this is exactly our research main aim. Related to this, we also investigate hiding secret information in communication protocols, namely Simple Object Access Protocol (SOAP) message, rather than in conventional digital files. To get a high steganographic capacity, two novel steganography methods were proposed. The first method was based on using 16x16 non-overlapping blocks and quantisation table for Joint Photographic Experts Group (JPEG) compression instead of 8x8. Then, the quality of JPEG stego images was enhanced by using optimised quantisation tables instead of the default tables. The second method, the hybrid method, was based on using optimised quantisation tables and two hiding techniques: JSteg along with our first proposed method. To increase the steganographic capacity, the impact of hiding data within image chrominance was investigated and explained. Since peak signal-to-noise ratio (PSNR) is extensively used as a quality measure of stego images, the reliability of PSNR for stego images was also evaluated in the work described in this thesis. Finally, to eliminate any detectable traces that traditional steganography may leave in stego files, a novel and undetectable steganography method based on SOAP messages was proposed. All methods proposed have been empirically validated as to indicate their utility and value. The results revealed that our methods and suggestions improved the main aspects of image steganography. Nevertheless, PSNR was found not to be a reliable quality evaluation measure to be used with stego image. On the other hand, information hiding in SOAP messages represented a distinctive way for undetectable and secret communication.EThOS - Electronic Theses Online ServiceMinistry of Higher Education in SyriaUniversity of AleppoGBUnited Kingdo

The Importance of Generalizability to Anomaly Detection

In security-related areas there is concern over novel “zero-day” attacks that penetrate system defenses and wreak havoc. The best methods for countering these threats are recognizing “nonself” as in an Artificial Immune System or recognizing “self” through clustering. For either case, the concern remains that something that appears similar to self could be missed. Given this situation, one could incorrectly assume that a preference for a tighter fit to self over generalizability is important for false positive reduction in this type of learning problem. This article confirms that in anomaly detection as in other forms of classification a tight fit, although important, does not supersede model generality. This is shown using three systems each with a different geometric bias in the decision space. The first two use spherical and ellipsoid clusters with a k-means algorithm modified to work on the one-class/blind classification problem. The third is based on wrapping the self points with a multidimensional convex hull (polytope) algorithm capable of learning disjunctive concepts via a thresholding constant. All three of these algorithms are tested using the Voting dataset from the UCI Machine Learning Repository, the MIT Lincoln Labs intrusion detection dataset, and the lossy-compressed steganalysis domain

An improved randomization of a multi-blocking jpeg based steganographic system.

Thesis (M.Sc.)-University of KwaZulu-Natal, Durban, 2010.Steganography is classified as the art of hiding information. In a digital context, this refers to our ability to hide secret messages within innocent digital cover data. The digital domain offers many opportunities for possible cover mediums, such as cloud based hiding (saving secret information within the internet and its structure), image based hiding, video and audio based hiding, text based documents as well as the potential of hiding within any set of compressed data. This dissertation focuses on the image based domain and investigates currently available image based steganographic techniques. After a review of the history of the field, and a detailed survey of currently available JPEG based steganographic systems, the thesis focuses on the systems currently considered to be secure and introduces mechanisms that have been developed to detect them. The dissertation presents a newly developed system that is designed to counter act the current weakness in the YASS JPEG based steganographic system. By introducing two new levels of randomization to the embedding process, the proposed system offers security benefits over YASS. The introduction of randomization to the B‐block sizes as well as the E‐block sizes used in the embedding process aids in increasing security and the potential for new, larger E‐block sizes also aids in providing an increased set of candidate coefficients to be used for embedding. The dissertation also introduces a new embedding scheme which focuses on hiding in medium frequency coefficients. By hiding in these medium frequency coefficients, we allow for more aggressive embedding without risking more visual distortion but trade this off with a risk of higher error rates due to compression losses. Finally, the dissertation presents simulation aimed at testing the proposed system performance compared to other JPEG based steganographic systems with similar embedding properties. We show that the new system achieves an embedding capacity of 1.6, which represents round a 7 times improvement over YASS. We also show that the new system, although introducing more bits in error per B‐block, successfully allows for the embedding of up to 2 bits per B‐block more than YASS at a similar error rate per B‐block. We conclude the results by demonstrating the new systems ability to resist detection both through human observation, via a survey, as well as resist computer aided analysis

An Analysis of Perturbed Quantization Steganography in the Spatial Domain

Steganography is a form of secret communication in which a message is hidden into a harmless cover object, concealing the actual existence of the message. Due to the potential abuse by criminals and terrorists, much research has also gone into the field of steganalysis - the art of detecting and deciphering a hidden message. As many novel steganographic hiding algorithms become publicly known, researchers exploit these methods by finding statistical irregularities between clean digital images and images containing hidden data. This creates an on-going race between the two fields and requires constant countermeasures on the part of steganographers in order to maintain truly covert communication. This research effort extends upon previous work in perturbed quantization (PQ) steganography by examining its applicability to the spatial domain. Several different information-reducing transformations are implemented along with the PQ system to study their effect on the security of the system as well as their effect on the steganographic capacity of the system. Additionally, a new statistical attack is formulated for detecting ± 1 embedding techniques in color images. Results from performing state-of-the-art steganalysis reveal that the system is less detectable than comparable hiding methods. Grayscale images embedded with message payloads of 0.4bpp are detected only 9% more accurately than by random guessing, and color images embedded with payloads of 0.2bpp are successfully detected only 6% more reliably than by random guessing

Détection statistique d'information cachée dans des images naturelles

La nécessité de communiquer de façon sécurisée n est pas chose nouvelle : depuis l antiquité des méthodes existent afin de dissimuler une communication. La cryptographie a permis de rendre un message inintelligible en le chiffrant, la stéganographie quant à elle permet de dissimuler le fait même qu un message est échangé. Cette thèse s inscrit dans le cadre du projet "Recherche d Informations Cachées" financé par l Agence Nationale de la Recherche, l Université de Technologie de Troyes a travaillé sur la modélisation mathématique d une image naturelle et à la mise en place de détecteurs d informations cachées dans les images. Ce mémoire propose d étudier la stéganalyse dans les images naturelles du point de vue de la décision statistique paramétrique. Dans les images JPEG, un détecteur basé sur la modélisation des coefficients DCT quantifiés est proposé et les calculs des probabilités du détecteur sont établis théoriquement. De plus, une étude du nombre moyen d effondrements apparaissant lors de l insertion avec les algorithmes F3 et F4 est proposée. Enfin, dans le cadre des images non compressées, les tests proposés sont optimaux sous certaines contraintes, une des difficultés surmontées étant le caractère quantifié des donnéesThe need of secure communication is not something new: from ancient, methods exist to conceal communication. Cryptography helped make unintelligible message using encryption, steganography can hide the fact that a message is exchanged.This thesis is part of the project "Hidden Information Research" funded by the National Research Agency, Troyes University of Technology worked on the mathematical modeling of a natural image and creating detectors of hidden information in digital pictures.This thesis proposes to study the steganalysis in natural images in terms of parametric statistical decision. In JPEG images, a detector based on the modeling of quantized DCT coefficients is proposed and calculations of probabilities of the detector are established theoretically. In addition, a study of the number of shrinkage occurring during embedding by F3 and F4 algorithms is proposed. Finally, for the uncompressed images, the proposed tests are optimal under certain constraints, a difficulty overcome is the data quantizationTROYES-SCD-UTT (103872102) / SudocSudocFranceF