Media objects are transformed into active, connected objects via identifiers embedded into them or their containers. In the context of a user's playback experience, a decoding process extracts the identifier from a media object and possibly additional context information and forwards it to a server. The server, in turn, maps the identifier to an action, such as returning metadata, re-directing the request to one or more other servers, requesting information from another server to identify the media object, etc. The linking process applies to broadcast objects as well as objects transmitted over networks in streaming and compressed file formats.

Connected audio and other media objects

The presently claimed invention generally relates to deriving and/or utilizing content signatures (e.g., so-called “fingerprints”). One claim recites a method of generating a fingerprint associated with a content item including: pseudo-randomly selecting a segment of the content item; and utilizing a processor or electronic processing circuitry, fingerprinting the selected segment of content item as at least an identifier of the content item. Of course, other claims and combination are provided as well.

Methods, Apparatus and Programs for Generating and Utilizing Content Signatures

In recent decades, we have witnessed the evolution of information technologies from the development of VLSI technologies, to communication and networking infrastructure, to the standardization of multimedia compression and coding schemes, to effective multimedia content search and retrieval. As a result, multimedia devices and digital content have become ubiquitous. This path of technological evolution has naturally led to a critical issue that must be addressed next, namely, to ensure that content, devices, and intellectual property are being used by authorized users for legitimate purposes, and to be able to forensically prove with high confidence when otherwise. When security is compromised, intellectual rights are violated, or authenticity is forged, forensic methodologies and tools are employed to reconstruct what has happened to digital content in order to answer who has done what, when, where, and how. The goal of this paper is to provide an overview on what has been done over the last decade in the new and emerging field of information forensics regarding theories, methodologies, state-of-the-art techniques, major applications, and to provide an outlook of the future.

http://sig.umd.edu/publications/Stamm_IEEEAccess_201305.pdf

Information Forensics: An Overview of the First Decade

Digital images are everywhere—from our cell phones to the pages of our online news sites. How we choose to use digital image processing raises a surprising host of legal and ethical questions that we must address. What are the ramifications of hiding data within an innocent imageq Is this an intentional security practice when used legitimately, or intentional deceptionq Is tampering with an image appropriate in cases where the image might affect public behaviorq Does an image represent a crime, or is it simply a representation of a scene that has never existedq Before action can even be taken on the basis of a questionable image, we must detect something about the image itself. Investigators from a diverse set of fields require the best possible tools to tackle the challenges presented by the malicious use of today's digital image processing techniques.In this survey, we introduce the emerging field of digital image forensics, including the main topic areas of source camera identification, forgery detection, and steganalysis. In source camera identification, we seek to identify the particular model of a camera, or the exact camera, that produced an image. Forgery detection's goal is to establish the authenticity of an image, or to expose any potential tampering the image might have undergone. With steganalysis, the detection of hidden data within an image is performed, with a possible attempt to recover any detected data. Each of these components of digital image forensics is described in detail, along with a critical analysis of the state of the art, and recommendations for the direction of future research.

/pdf/vision-of-the-unseen-current-trends-and-challenges-in-n3zatucgx0.pdf

Vision of the unseen: Current trends and challenges in digital image and video forensics

Methods and apparatus for embedding digital watermarks into a digital host content are provided. A digital host content is received, e.g., at a receiver or other device incorporating a receiver. One or more watermark embedding technologies is selected. Multiple embedding opportunities are identified within the host content. A subset of the identified embedding opportunities is selected. A multiplicity of digital watermarks are then embedded into the host content in accordance with the selected subset of embedding opportunities utilizing the one or more selected watermark embedding technologies. The selecting of the subset of embedding opportunities may be adapted to provide a desired tradeoff between levels of robustness, security, and transparency of the watermark. A plurality of watermarking embedding technologies may be selected and used in the embedding step.

Security enhancements of digital watermarks for multi-media content

Publisher Summary
This chapter focuses on a specific data-hiding application—steganography. As opposed to digital watermarking, the main property of steganography is statistical undetectability of embedded data. The payload is usually unrelated to the cover Work, which only serves as a decoy. The information-theoretic definition of steganographic security (Cachin's definition) is the most widely used definition in practice. It is usually applied in a simplified form by accepting a model for the cover Work. Secure steganographic schemes must take into account steganalytic methods. One possibility is to replace the embedding operation of LSB flipping (F5) to avoid introducing easily detectable artifacts. Another possibility is to mask the embedding distortion as a naturally occurring phenomenon, such as during image acquisition (stochastic modulation). Alternatively, one can design schemes that preserve some vital statistical characteristics of the cover image (OutGuess) or a model of the cover that is recoverable from the stego Work (model-based steganography). In a typical steganographic scheme, the placement of embedding changes (the selection rule) is shared between the sender and the recipient. However, there are many situations when this information cannot be shared, such as in adaptive steganography, selection rules determined from side information, or in public-key steganography. The problem of nonshared selection rules is equivalent to writing in memory with defective cells and can be efficiently approached using sparse linear codes, known as LT codes.

Chapter 12 – Steganography

Publisher Summary
The robustness of a watermarking method is a measure of the ability of the watermark to survive legitimate and everyday usage of the content. This chapter presents general methods for achieving high robustness along with specific methods for handling some of the most common types of processing. In designing a robust watermark, it is important to identify the specific processes that are likely to occur between embedding and detection. Robustness to a given process often comes at some expense in computational cost, data payload, fidelity, or even the robustness of some other process. It is, therefore, wise to ignore those processes that are unlikely in a given application. Further, this chapter analyzes the effects of some valumetric distortions (that is, distortions that change the values of individual pixels or audio samples). Common valumetric distortions that occur to photographs, music, and video can often be modeled as combinations of additive noise, amplitude changes, linear filtering, and/or quantization. Temporal and geometric distortions are also discussed such as delay, translation, rotation, and scaling.

8 – Robust Watermarking

For each small image region (in space and time), a measure of perceptual transparence of each of a set of possible watermark carrier modulations is used to choose a subset of such modulations, from which a secure random number generator selects, for each image region, a single carrier, modulations of which carry the watermark data.

Secure robust high-fidelity watermarking

Forensic digital watermarking is a promising tool in the fight against piracy of copyrighted motion imagery content, but to be effective it must be (1) imperceptibly embedded in high-definition motion picture source, (2) reliably retrieved, even from degraded copies as might result from camcorder capture and subsequent very-low-bitrate compression and distribution on the Internet, and (3) secure against unauthorized removal. No existing watermarking technology has yet to meet these three simultaneous requirements of fidelity, robustness, and security. We describe here a forensic watermarking approach that meets all three requirements. It is based on the inherent robustness and imperceptibility of very low spatiotemporal frequency watermark carriers, and on a watermark placement technique that renders jamming attacks too costly in picture quality, even if the attacker has complete knowledge of the embedding algorithm. The algorithm has been tested on HD Cinemascope source material exhibited in a digital cinema viewing room. The watermark is imperceptible, yet recoverable after exhibition capture with camcorders, and after the introduction of other distortions such as low-pass filtering, noise addition, geometric shifts, and the manipulation of brightness and contrast.© (2003) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Robust content-dependent high-fidelity watermark for tracking in digital cinema

One of the major hurdles in maintaining long-lived electronic systems is that electronic parts become obsolete, no longer available from the original suppliers. When this occurs, an engineer is tasked with resolving the problem by finding a replacement that is "as similar as possible" to the original part. The current approach involves a laborious manual search through several electronic portals and data books. The search is difficult because potential replacements may differ from the original and from each other by one or more parameters. Worse still, the cumbersome nature of this process may cause the engineers to miss appropriate solutions amid the many thousands of parts listed in industry catalogs.In this paper, we address this problem by introducing the notion of a parametric "distance" between electronic components. We use this distance to search a large parts data set and recommend likely replacements. Recommendations are based on an adaptive nearest-neighbor search through the parametric data set. For each user, we learn how to scale the axes of the feature space in which the nearest neighbors are sought. This allows the system to learn each user's judgment of the phrase "as similar as possible."

Jeffrey A. Bloom

Papers

Chapter 12 – Steganography

8 – Robust Watermarking

Secure robust high-fidelity watermarking

Robust content-dependent high-fidelity watermark for tracking in digital cinema

An adaptive nearest neighbor search for a parts acquisition ePortal