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Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio, and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is always to conceal the very existence of the embedded data. Steganography has various useful applications. However, like any other science it can be used for ill intentions. It has been propelled to the forefront of current security techniques by the remarkable growth in computational power, the increase in security awareness by, e.g., individuals, groups, agencies, government and through intellectual pursuit. Steganography's ultimate objectives, which are undetectability, robustness (resistance to various image processing methods and compression) and capacity of the hidden data, are the main factors that separate it from related techniques such as watermarking and cryptography. This paper provides a state-of-the-art review and analysis of the different existing methods of steganography along with some common standards and guidelines drawn from the literature. This paper concludes with some recommendations and advocates for the object-oriented embedding mechanism. Steganalysis, which is the science of attacking steganography, is not the focus of this survey but nonetheless will be briefly discussed.

Challenges face biometrics researchers and particularly those who are dealing with skin tone detection include choosing a colour space, generating the skin model and processing the obtained regions to fit applications. The majority of existing methods have in common the de-correlation of luminance from the considered colour channels. Luminance is underestimated since it is seen as the least contributing colour component to skin colour detection. This work questions this claim by showing that luminance can be useful in the segregation of skin and non-skin clusters. To this end, here we use a new colour space which contains error signals derived from differentiating the grayscale map and the non-red encoded grayscale version. The advantages of the approach are the reduction of space dimensionality from 3D, RGB, to 1D space advocating its unfussiness and the construction of a rapid classifier necessary for real time applications. The proposed method generates a 1D space map without prior knowledge of the host image. A comprehensive experimental test was conducted and initial results are presented. This paper also discusses an application of the method to image steganography where it is used to orient the embedding process since skin information is deemed to be psycho-visually redundant.

The recent digital revolution has facilitated communication, data portability and on-the-fly manipulation. Unfortunately, this has brought along some critical security vulnerabilities that put digital documents at risk. The problem is in the security mechanism adopted to secure these documents by means of encrypted passwords; however, this security shield does not actually protect the documents which are stored intact. We propose here a solution to this real world problem through a 1D hash algorithm coupled with 2D iFFT (irreversible Fast Fourier Transform) to encrypt digital documents in the 2D spatial domain. Further by applying an imperceptible information hiding technique we can add another security layer which is resistant to noise and to a certain extent JPEG compression. We support this assertion by showing a practical example which is drawn from our set of experiments. This work exploits Jarvis' kernel to generate the error diffusion signal and the Wavelet-based Inverse Halftoning via De-convolution (WInHD) to recover the approximation of the original signal. Our method not only points out forgery but also allows legal or forensics expert gain access to the original document despite being manipulated. This would undoubtedly be very useful in cases of disputes or claims.