Vers l’anti-criminalistique en images numériques via la restauration d’images

Image forensics enjoys its increasing popularity as a powerful image authentication tool, working in a blind passive way without the aid of any a priori embedded information compared to fragile image watermarking. On its opponent side, image anti-forensics attacks forensic algorithms for the future development of more trustworthy forensics. When image coding or processing is involved, we notice that image anti-forensics to some extent shares a similar goal with image restoration. Both of them aim to recover the information lost during the image degradation, yet image anti-forensics has one additional indispensable forensic undetectability requirement. In this thesis, we form a new research line for image anti-forensics, by leveraging on advanced concepts/methods from image restoration meanwhile with integrations of anti-forensic strategies/terms. Under this context, this thesis contributes on the following four aspects for JPEG compression and median filtering anti-forensics: (i) JPEG anti-forensics using Total Variation based deblocking, (ii) improved Total Variation based JPEG anti-forensics with assignment problem based perceptual DCT histogram smoothing, (iii) JPEG anti-forensics using JPEG image quality enhancement based on a sophisticated image prior model and non-parametric DCT histogram smoothing based on calibration, and (iv) median filtered image quality enhancement and anti-forensics via variational deconvolution. Experimental results demonstrate the effectiveness of the proposed anti-forensic methods with a better forensic undetectability against existing forensic detectors as well as a higher visual quality of the processed image, by comparisons with the state-of-the-art methods.La criminalistique en images numériques se développe comme un outil puissant pour l'authentification d'image, en travaillant de manière passive et aveugle sans l'aide d'informations d'authentification pré-intégrées dans l'image (contrairement au tatouage fragile d'image). En parallèle, l'anti-criminalistique se propose d'attaquer les algorithmes de criminalistique afin de maintenir une saine émulation susceptible d'aider à leur amélioration. En images numériques, l'anti-criminalistique partage quelques similitudes avec la restauration d'image : dans les deux cas, l'on souhaite approcher au mieux les informations perdues pendant un processus de dégradation d'image. Cependant, l'anti-criminalistique se doit de remplir au mieux un objectif supplémentaire, extit{i.e.} : être non détectable par la criminalistique actuelle. Dans cette thèse, nous proposons une nouvelle piste de recherche pour la criminalistique en images numériques, en tirant profit des concepts/méthodes avancés de la restauration d'image mais en intégrant des stratégies/termes spécifiquement anti-criminalistiques. Dans ce contexte, cette thèse apporte des contributions sur quatre aspects concernant, en criminalistique JPEG, (i) l'introduction du déblocage basé sur la variation totale pour contrer les méthodes de criminalistique JPEG et (ii) l'amélioration apportée par l'adjonction d'un lissage perceptuel de l'histogramme DCT, (iii) l'utilisation d'un modèle d'image sophistiqué et d'un lissage non paramétrique de l'histogramme DCT visant l'amélioration de la qualité de l'image falsifiée; et, en criminalistique du filtrage médian, (iv) l'introduction d'une méthode fondée sur la déconvolution variationnelle. Les résultats expérimentaux démontrent l'efficacité des méthodes anti-criminalistiques proposées, avec notamment une meilleure indétectabilité face aux détecteurs criminalistiques actuels ainsi qu'une meilleure qualité visuelle de l'image falsifiée par rapport aux méthodes anti-criminalistiques de l'état de l'art

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Fundamental Limits in Multimedia Forensics and Anti-forensics

As the use of multimedia editing tools increases, people become questioning the authenticity of multimedia content. This is specially a big concern for authorities, such as law enforcement, news reporter and government, who constantly use multimedia evidence to make critical decisions. To verify the authenticity of multimedia content, many forensic techniques have been proposed to identify the processing history of multimedia content under question. However, as new technologies emerge and more complicated scenarios are considered, the limitation of multimedia forensics has been gradually realized by forensic researchers. It is the inevitable trend in multimedia forensics to explore the fundamental limits. In this dissertation, we propose several theoretical frameworks to study the fundamental limits in various forensic problems. Specifically, we begin by developing empirical forensic techniques to deal with the limitation of existing techniques due to the emergence of new technology, compressive sensing. Then, we go one step further to explore the fundamental limit of forensic performance. Two types of forensic problems have been examined. In operation forensics, we propose an information theoretical framework and define forensicability as the maximum information features contain about hypotheses of processing histories. Based on this framework, we have found the maximum number of JPEG compressions one can detect. In order forensics, an information theoretical criterion is proposed to determine when we can and cannot detect the order of manipulation operations that have been applied on multimedia content. Additionally, we have examined the fundamental tradeoffs in multimedia antiforensics, where attacking techniques are developed by forgers to conceal manipulation fingerprints and confuse forensic investigations. In this field, we have defined concealability as the effectiveness of anti-forensics concealing manipulation fingerprints. Then, a tradeoff between concealability, rate and distortion is proposed and characterized for compression anti-forensics, which provides us valuable insights of how forgers may behave under their best strategy

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

Improving Security and Performance in Low Latency Anonymous Networks

Conventional wisdom dictates that the level of anonymity offered by low latency anonymity networks increases as the user base grows. However, the most significant obstacle to increased adoption of such systems is that their security and performance properties are perceived to be weak. In an effort to help foster adoption, this dissertation aims to better understand and improve security, anonymity, and performance in low latency anonymous communication systems. To better understand the security and performance properties of a popular low latency anonymity network, we characterize Tor, focusing on its application protocol distribution, geopolitical client and router distributions, and performance. For instance, we observe that peer-to-peer file sharing protocols use an unfair portion of the network’s scarce bandwidth. To reduce the congestion produced by bulk downloaders in networks such as Tor, we design, implement, and analyze an anonymizing network tailored specifically for the BitTorrent peer-to-peer file sharing protocol. We next analyze Tor’s security and anonymity properties and empirically show that Tor is vulnerable to practical end-to-end traffic correlation attacks launched by relatively weak adversaries that inflate their bandwidth claims to attract traffic and thereby compromise key positions on clients’ paths. We also explore the security and performance trade-offs that revolve around path length design decisions and we show that shorter paths offer performance benefits and provide increased resilience to certain attacks. Finally, we discover a source of performance degradation in Tor that results from poor congestion and flow control. To improve Tor’s performance and grow its user base, we offer a fresh approach to congestion and flow control inspired by techniques from IP and ATM networks

Framework for privacy-aware content distribution in peer-to- peer networks with copyright protection

The use of peer-to-peer (P2P) networks for multimedia distribution has spread out globally in recent years. This mass popularity is primarily driven by the efficient distribution of content, also giving rise to piracy and copyright infringement as well as privacy concerns. An end user (buyer) of a P2P content distribution system does not want to reveal his/her identity during a transaction with a content owner (merchant), whereas the merchant does not want the buyer to further redistribute the content illegally. Therefore, there is a strong need for content distribution mechanisms over P2P networks that do not pose security and privacy threats to copyright holders and end users, respectively. However, the current systems being developed to provide copyright and privacy protection to merchants and end users employ cryptographic mechanisms, which incur high computational and communication costs, making these systems impractical for the distribution of big files, such as music albums or movies.El uso de soluciones de igual a igual (peer-to-peer, P2P) para la distribución multimedia se ha extendido mundialmente en los últimos años. La amplia popularidad de este paradigma se debe, principalmente, a la distribución eficiente de los contenidos, pero también da lugar a la piratería, a la violación del copyright y a problemas de privacidad. Un usuario final (comprador) de un sistema de distribución de contenidos P2P no quiere revelar su identidad durante una transacción con un propietario de contenidos (comerciante), mientras que el comerciante no quiere que el comprador pueda redistribuir ilegalmente el contenido más adelante. Por lo tanto, existe una fuerte necesidad de mecanismos de distribución de contenidos por medio de redes P2P que no supongan un riesgo de seguridad y privacidad a los titulares de derechos y los usuarios finales, respectivamente. Sin embargo, los sistemas actuales que se desarrollan con el propósito de proteger el copyright y la privacidad de los comerciantes y los usuarios finales emplean mecanismos de cifrado que implican unas cargas computacionales y de comunicaciones muy elevadas que convierten a estos sistemas en poco prácticos para distribuir archivos de gran tamaño, tales como álbumes de música o películas.L'ús de solucions d'igual a igual (peer-to-peer, P2P) per a la distribució multimèdia s'ha estès mundialment els darrers anys. L'àmplia popularitat d'aquest paradigma es deu, principalment, a la distribució eficient dels continguts, però també dóna lloc a la pirateria, a la violació del copyright i a problemes de privadesa. Un usuari final (comprador) d'un sistema de distribució de continguts P2P no vol revelar la seva identitat durant una transacció amb un propietari de continguts (comerciant), mentre que el comerciant no vol que el comprador pugui redistribuir il·legalment el contingut més endavant. Per tant, hi ha una gran necessitat de mecanismes de distribució de continguts per mitjà de xarxes P2P que no comportin un risc de seguretat i privadesa als titulars de drets i els usuaris finals, respectivament. Tanmateix, els sistemes actuals que es desenvolupen amb el propòsit de protegir el copyright i la privadesa dels comerciants i els usuaris finals fan servir mecanismes d'encriptació que impliquen unes càrregues computacionals i de comunicacions molt elevades que fan aquests sistemes poc pràctics per a distribuir arxius de grans dimensions, com ara àlbums de música o pel·lícules

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas