Perfectly secure steganography: hiding information in the quantum noise of a photograph

We show that the quantum nature of light can be used to hide a secret message within a photograph. Using this physical principle we achieve information-theoretic secure steganography, which had remained elusive until now. The protocol is such that the digital picture in which the secret message is embedded is perfectly undistinguishable from an ordinary photograph. This implies that, on a fundamental level, it is impossible to discriminate a private communication from an exchange of photographs.Comment: 5 pages, 3 figures + appendix : 5 pages, 6 figure

Hard Communication Channels for Steganography

This paper considers steganography - the concept of hiding the presence of secret messages in legal communications - in the computational setting and its relation to cryptography. Very recently the first (non-polynomial time) steganographic protocol has been shown which, for any communication channel, is provably secure, reliable, and has nearly optimal bandwidth. The security is unconditional, i.e. it does not rely on any unproven complexity-theoretic assumption. This disproves the claim that the existence of one-way functions and access to a communication channel oracle are both necessary and sufficient conditions for the existence of secure steganography in the sense that secure and reliable steganography exists independently of the existence of one-way functions. In this paper, we prove that this equivalence also does not hold in the more realistic setting, where the stegosystem is polynomial time bounded. We prove this by constructing (a) a channel for which secure steganography exists if and only if one-way functions exist and (b) another channel such that secure steganography implies that no one-way functions exist. We therefore show that security-preserving reductions between cryptography and steganography need to be treated very carefully

Provably secure and efficient audio compression based on compressive sensing

The advancement of systems with the capacity to compress audio signals and simultaneously secure is a highly attractive research subject. This is because of the need to enhance storage usage and speed up the transmission of data, as well as securing the transmission of sensitive signals over limited and insecure communication channels. Thus, many researchers have studied and produced different systems, either to compress or encrypt audio data using different algorithms and methods, all of which suffer from certain issues including high time consumption or complex calculations. This paper proposes a compressing sensing-based system that compresses audio signals and simultaneously provides an encryption system. The audio signal is segmented into small matrices of samples and then multiplied by a non-square sensing matrix generated by a Gaussian random generator. The reconstruction process is carried out by solving a linear system using the pseudoinverse of Moore-Penrose. The statistical analysis results obtaining from implementing different types and sizes of audio signals prove that the proposed system succeeds in compressing the audio signals with a ratio reaching 28% of real size and reconstructing the signal with a correlation metric between 0.98 and 0.99. It also scores very good results in the normalized mean square error (MSE), peak signal-to-noise ratio metrics (PSNR), and the structural similarity index (SSIM), as well as giving the signal a high level of security

Conditional Entrench Spatial Domain Steganography

Steganography is a technique of concealing the secret information in a digital carrier media, so that only the authorized recipient can detect the presence of secret information. In this paper, we propose a spatial domain steganography method for embedding secret information on conditional basis using 1-Bit of Most Significant Bit (MSB). The cover image is decomposed into blocks of 8*8 matrix size. The first block of cover image is embedded with 8 bits of upper bound and lower bound values required for retrieving payload at the destination. The mean of median values and difference between consecutive pixels of each 8*8 block of cover image is determined to embed payload in 3 bits of Least Significant Bit (LSB) and 1 bit of MSB based on prefixed conditions. It is observed that the capacity and security is improved compared to the existing methods with reasonable PSNR