A survey on passive digital video forgery detection techniques

Digital media devices such as smartphones, cameras, and notebooks are becoming increasingly popular. Through digital platforms such as Facebook, WhatsApp, Twitter, and others, people share digital images, videos, and audio in large quantities. Especially in a crime scene investigation, digital evidence plays a crucial role in a courtroom. Manipulating video content with high-quality software tools is easier, which helps fabricate video content more efficiently. It is therefore necessary to develop an authenticating method for detecting and verifying manipulated videos. The objective of this paper is to provide a comprehensive review of the passive methods for detecting video forgeries. This survey has the primary goal of studying and analyzing the existing passive techniques for detecting video forgeries. First, an overview of the basic information needed to understand video forgery detection is presented. Later, it provides an in-depth understanding of the techniques used in the spatial, temporal, and spatio-temporal domain analysis of videos, datasets used, and their limitations are reviewed. In the following sections, standard benchmark video forgery datasets and the generalized architecture for passive video forgery detection techniques are discussed in more depth. Finally, identifying loopholes in existing surveys so detecting forged videos much more effectively in the future are discussed

Scene Segmentation for Interframe Forgery Identification

A common type of video forgery is inter-frame forgery, which occurs in the temporal domain, such as frame duplication, frame insertion, and frame deletion. Some existing methods are not effective to detect forgeries in static scenes. This work proposes static and dynamic scene segmentation and performs forgery detection for each scene. Scene segmentation is performed for outlier detection based on changes of optical flow. Various similarity checks are performed to find the correlation for each frame. The experimental results showed that the proposed method is effective in identifying forgeries in various scenes, especially static scenes, compared with existing methods

Scene Segmentation for Interframe Forgery Identification

A common type of video forgery is inter-frame forgery, which occurs in the temporal domain, such as frame duplication, frame insertion, and frame deletion. Some existing methods are not effective to detect forgeries in static scenes. This work proposes static and dynamic scene segmentation and performs forgery detection for each scene. Scene segmentation is performed for outlier detection based on changes of optical flow. Various similarity checks are performed to find the correlation for each frame. The experimental results showed that the proposed method is effective in identifying forgeries in various scenes, especially static scenes, compared with existing methods

Handbook of Digital Face Manipulation and Detection

This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area

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

Handbook of Digital Face Manipulation and Detection

This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area

Natural Image Statistics for Digital Image Forensics

We describe a set of natural image statistics that are built upon two multi-scale image decompositions, the quadrature mirror filter pyramid decomposition and the local angular harmonic decomposition. These image statistics consist of first- and higher-order statistics that capture certain statistical regularities of natural images. We propose to apply these image statistics, together with classification techniques, to three problems in digital image forensics: (1) differentiating photographic images from computer-generated photorealistic images, (2) generic steganalysis; (3) rebroadcast image detection. We also apply these image statistics to the traditional art authentication for forgery detection and identification of artists in an art work. For each application we show the effectiveness of these image statistics and analyze their sensitivity and robustness

Scientific, Technical, and Forensic Evidence

Materials from the conference on Scientific, Technical, and Forensic Evidence held by UK/CLE in February 2002

A non-destructive technical and stylistic comparative analysis of selected metal artefacts from the Ditsong National Museum of Cultural History

The destructive nature of conventional analytical techniques, coupled with the finite nature of ancient/historical artefacts, has long restricted technical examinations of museum collections, mainly due to ethical constraints. However, over the past few decades, the application of Non-Destructive Evaluation (NDE) techniques has become increasingly popular within the fields of archaeology and cultural heritage diagnostics. The application of such techniques has facilitated the examination of objects that have long remained uninvestigated. However, this positive development also held a slight drawback, in that researchers tend to now focus on technical analyses alone, while excluding more traditional means of analyses, such as comparative stylistic analysis and surface investigation. By employing a combination of stylistic analysis, visual surface investigation (by means of SLR photography and digital microscopy) and nuclear imaging (by means of Microfocus X-Ray Computed Tomography), the thesis sets out to justify the application of mixed methodologies as part of a more holistic integrated authentication approach. Thus stated, the thesis presents a mixed-methodological approach towards the analysis of selected metal objects from the Ditsong National Museum of Cultural History in Pretoria, South Africa. The objects under investigation include a small collection of ancient Egyptian bronze statuettes, a Samurai helmet (kabuto) and mask (menpó), a European gauntlet, and an Arabian dagger (jambiya/khanjar). While all the objects are curated as part of the museum’s archaeology and military history collections, the exact production dates, manufacturing techniques and areas of origin remain a mystery. By using a combination of techniques, the thesis aims to identify diagnostic features that can be used to shed light on their relative age, culturo-chronological framework and, by extension, their authenticity.Old Testament and Ancient Near Eastern Studie