A concise and accessible guide to techniques for detecting doctored and fake images in photographs and digital media. Stalin, Mao, Hitler, Mussolini, and other dictators routinely doctored photographs so that the images aligned with their messages. They erased people who were there, added people who were not, and manipulated backgrounds. They knew if they changed the visual record, they could change history. Once, altering images required hours in the darkroom; today, it can be done with a keyboard and mouse. Because photographs are so easily faked, fake photos are everywhere—supermarket tabloids, fashion magazines, political ads, and social media. How can we tell if an image is real or false? In this volume in the MIT Press Essential Knowledge series, Hany Farid offers a concise and accessible guide to techniques for detecting doctored and fake images in photographs and digital media. Farid, an expert in photo forensics, has spent two decades developing techniques for authenticating digital images. These techniques model the entire image-creation process in order to find the digital disruption introduced by manipulation of the image. Each section of the book describes a different technique for analyzing an image, beginning with those requiring minimal technical expertise and advancing to those at intermediate and higher levels. There are techniques for, among other things, reverse image searches, metadata analysis, finding image imperfections introduced by JPEG compression, image cloning, tracing pixel patterns, and detecting images that are computer generated. In each section, Farid describes the techniques, explains when they should be applied, and offers examples of image analysis.

How do you grow a spaghetti tree? Who saw fairies down by the creek? A fake is something that is not what it seems to be. Fakes are meant to trick people.

Photographs of contemporary Veles are intertwined with fragments from an archaeological discovery also called 'the Book of Veles' -- a cryptic collection of 40 'ancient' wooden boards discovered in Russia in 1919, written in a proto-Slavic language. It was claimed to be a history of the Slavic people and the god Veles himself--the pre-Christian Slavic god of mischief, chaos and deception

The first comprehensive and detailed presentation of techniques for authenticating digital images. Photographs have been doctored since photography was invented. Dictators have erased people from photographs and from history. Politicians have manipulated photos for short-term political gain. Altering photographs in the predigital era required time-consuming darkroom work. Today, powerful and low-cost digital technology makes it relatively easy to alter digital images, and the resulting fakes are difficult to detect. The field of photo forensics—pioneered in Hany Farid's lab at Dartmouth College—restores some trust to photography. In this book, Farid describes techniques that can be used to authenticate photos. He provides the intuition and background as well as the mathematical and algorithmic details needed to understand, implement, and utilize a variety of photo forensic techniques. Farid traces the entire imaging pipeline. He begins with the physics and geometry of the interaction of light with the physical world, proceeds through the way light passes through a camera lens, the conversion of light to pixel values in the electronic sensor, the packaging of the pixel values into a digital image file, and the pixel-level artifacts introduced by photo-editing software. Modeling the path of light during image creation reveals physical, geometric, and statistical regularities that are disrupted during the creation of a fake. Various forensic techniques exploit these irregularities to detect traces of tampering. A chapter of case studies examines the authenticity of viral video and famously questionable photographs including “Golden Eagle Snatches Kid” and the Lee Harvey Oswald backyard photo.

Mobile crowdsensing is a technology that allows large scale, cost-effective sensing of the physical world. In mobile crowdsensing, mobile personal devices such as smart phones or smart watches come equipped with a variety of sensors that can be leveraged to collect data related to environment, transportation, healthcare, safety and so on. This book presents the first extensive coverage of mobile crowdsensing, with examples and insights drawn from the authors’ extensive research on this topic as well as from the research and development of a growing community of researchers and practitioners working in this emerging field. Throughout the text, the authors provide the reader with various examples of crowdsensing applications and the building blocks to creating the necessary infrastructure, explore the related concepts of mobile sensing and crowdsourcing, and examine security and privacy issues introduced by mobile crowdsensing platforms. Provides a comprehensive description of mobile crowdsensing, a one-stop shop for all relevant issues pertaining to mobile crowdsensing, including motivation, applications, design and implementation, incentive mechanisms, and reliability and privacy. Describes the design and implementations of mobile crowdsensing platforms of great interest for the readers working in research and industry to quickly implement and test their systems. Identifies potential issues in building such mobile crowdsensing applications to ensure their usability in real life and presents future directions in mobile crowdsensing by emphasizing the open problems that have to be addressed.

Deep Fakes: Algorithms and Society focuses on the use of artificial intelligence technologies to produce fictitious photorealistic audiovisual clips that are indistinguishable from traditional video media. For over a century, the indexical relationship of the photographic image, and its related media of film and video, to the scene of capture has served as a basis for truth claims. Historically, the iconicity of these images has featured a causal traceback to actual light rays in a particular time and space, which were fixed by chemical reactions or digital sensors to the resultant image. Today, photorealistic audiovisual media can be generated from deep learning networks that sever any connection to an actual event. Should society instantiate new regimes to manage this new challenge to our sense of reality and the traditional evidential capacities of the ‘mechanical image’? How do these images generate information disorder while also providing the basis for legitimate tools used in entertainment and creative industries? Scholars and students from many backgrounds, as well as policymakers, journalists and the general reading public, will find a multidisciplinary approach to questions posed by deep fake research from Communication, International Studies, Writing and Rhetoric.

Describes the different ways con artists use fraud to get money, including stealing identities, copying paintings, and counterfeiting money, and how they are caught.