Benchmarking Steganalysis

This chapter discusses how to evaluate the effectiveness of steganalysis techniques. In the steganalysis literature, numerous different methods are used to measure detection accuracy, with different authors using incompatible benchmarks. Thus it is difficult to make a fair comparison of competing steganalysis methods. This chapter argues that some of the choices for steganalysis benchmarks are demonstrably poor, either in statistical foundation or by over-valuing irrelevant areas of the performance envelope. Good choices of benchmark are highlighted, and simple statistical techniques demonstrated for evaluating the significance of observed performance differences. It is hoped that this chapter will make practitioners and steganalysis researchers better able to evaluate the quality of steganography detection methods.

Computational Aspects of Digital Steganography

This chapter provides an overview, based on current research, on theoretical aspects of digital steganography— a relatively new field of computer science that deals with hiding secret data in unsuspicious cover media. We focus on formal analysis of security of steganographic systems from a computational complexity point of view and provide models of secure systems that make realistic assumptions of limited computational resources of involved parties. This allows us to look at steganographic secrecy based on reasonable complexity assumptions similar to ones commonly accepted in modern cryptography. In this chapter we expand the analyses of stego-systems beyond security aspects, which practitioners find difficult to implement (if not impossible to realize), to the question why such systems are so difficult to implement and what makes these systems different from practically used ones.

Visibility Control and Quality Assessment of Watermarking and Data Hiding Algorithms

In watermarking and data hiding context, it may be very useful to have methods checking the invisibility of the inserted data or at least, checking the objective quality after the mark embedding or after an attack on the watermarked media. Many works exist in the literature dealing with quality assessment mainly focused on compression application. Nevertheless, visual quality assessment should include special requirements that depend on the application context. This chapter presents an extended review of both subjective and objective quality assessment of images and video in the field of watermarking and data hiding applications.

Digital Video Watermarking and the Collusion Attack

This chapter is devoted to the analysis of the collusion attack applied to current digital video watermarking algorithms. In particular, we analyze the effects of collusion attacks, with particular attention to the temporal frame averaging (TFA), applied to two basic watermarking systems like spread spectrum (SS) and spread transform dither modulation (STDM). The chapter describes the main drawbacks and advantages in using these two watermarking schemes and, above all, the fundamental issues to be taken into account to grant a certain level of robustness when a collusion attack is carried out by an attacker.

Authentication Watermarkings for Binary Images

Data hiding (DH) is a technique used to embed a sequence of bits in a cover image with small visual deterioration and the means to extract it afterwards. Authentication watermarking (AW) techniques use DH to insert particular data into an image, in order to detect later any accidental or malicious alterations in the image, as well as to certify that the image came from the right source. In recent years, some AWs for binary images have been proposed in the literature. The authentication of binary images is necessary in practice, because most scanned and computer-generated document images are binary.This publication describes techniques and theories involved in binary image AW: We describe DH techniques for binary images and analyze which of them are adequate to be used in AWs; analyze the most adequate secret- and public-key cryptographic ciphers for the AWs; describe how to spatially localize the alteration in the image (besides detecting it) without compromising the security; present AWs forJBIG2-compressed binary images; present a reversible AW for binary images; and finally present our conclusions and future research.

Efficient Transparent JPEG2000 Encryption

In this chapter we investigate two different techniques for transparent/perceptual encryption of JPEG2000 files or bitstreams in the context of digital rights management (DRM) schemes. These methods are efficient in the sense of minimizing the computational costs of encryption. A classical bitstream-based approach employing format-compliant encryption of packet body data is compared to a compression-integrated technique that uses the concept of secret transform domains, in our case a wavelet packet transform.

Digital Watermarking in the Transform Domain with Emphasis on SVD

The chapter illustrates watermarking based on the transform domain. It argues that transform-based watermarking is robust to possible attacks and imperceptible with respect to the quality of the multimedia file we would like to protect. Among those transforms commonly used in communications, we emphasize the use of singular value decomposition (SVD) for digital watermarking. The main advantage of this choice is flexibility of application. In fact, SVD may be applied in several fields where data are organized as matrices, including multimedia and communications. We present a robust SVD-based watermarking scheme for images. According to the detection steps, the watermark can be determined univocally, while other related works present flaws in watermark detection. A case study of our approach refers to the protection of geographical and spatial data in case of the raster representation model of maps.

Statistical Watermark Detection in the Transform Domain for Digital Images

The problem of multiplicative watermark detection in digital images can be viewed as a binary decision where the observation is the possibility that watermarked samples can be thought of as a noisy environment in which a desirable signal, called watermark, may exist. In this chapter, we investigate the optimum watermark detection from the viewpoint of decision theory. Different transform domains are considered with generalized noise models. We study the effect of the watermark strength on both the detector performance and the imperceptibility of the host image. Also, the robustness issue is addressed while considering a number of commonly used attacks.

Steganalysis

In this chapter we provide a detailed overview of the state of the art in steganalysis. Performance of some steganalysis techniques are compared based on critical parameters such as the hidden message detection probability, accuracy of the estimated hidden message length and secret key, and so forth. We also provide an overview of some shareware/freeware steganographic tools. Some open problems in steganalysis are described.

On Noise, Steganography, and the Active Warden

Modern digital steganography has evolved a number of techniques to embed information near invisibly into digital media. Many of the techniques for information hiding result in a set of changes to the cover image that appear, for all intents and purposes to be noise. This chapter presents information for the reader to understand how noise is intentionally and unintentionally used in information hiding. This chapter first reviews a series of noise-like steganography methods. From these techniques the problems faced by the active warden can be posed in a systematic way. Results of using advanced clean image estimation techniques for active warden based steganalysis are presented. This chapter is concluded with a discussion of the future of steganography.