A novel steganography approach for audio files

We present a novel robust and secure steganography technique to hide images into audio files aiming at increasing the carrier medium capacity. The audio files are in the standard WAV format, which is based on the LSB algorithm while images are compressed by the GMPR technique which is based on the Discrete Cosine Transform (DCT) and high frequency minimization encoding algorithm. The method involves compression-encryption of an image file by the GMPR technique followed by hiding it into audio data by appropriate bit substitution. The maximum number of bits without significant effect on audio signal for LSB audio steganography is 6 LSBs. The encrypted image bits are hidden into variable and multiple LSB layers in the proposed method. Experimental results from observed listening tests show that there is no significant difference between the stego audio reconstructed from the novel technique and the original signal. A performance evaluation has been carried out according to quality measurement criteria of Signal-to-Noise Ratio (SNR) and Peak Signal-to-Noise Ratio (PSNR)

Image data hiding

Image data hiding represents a class of processes used to embed data into cover images. Robustness is one of the basic requirements for image data hiding. In the first part of this dissertation, 2D and 3D interleaving techniques associated with error-correction-code (ECC) are proposed to significantly improve the robustness of hidden data against burst errors. In most cases, the cover image cannot be inverted back to the original image after the hidden data are retrieved. In this dissertation, one novel reversible (lossless) data hiding technique is then introduced. This technique is based on the histogram modification, which can embed a large amount of data while keeping a very high visual quality for all images. The performance is hence better than most existing reversible data hiding algorithms. However, most of the existing lossless data hiding algorithms are fragile in the sense that the hidden data cannot be extracted correctly after compression or small alteration. In the last part of this dissertation, we then propose a novel robust lossless data hiding technique based on patchwork idea and spatial domain pixel modification. This technique does not generate annoying salt-pepper noise at all, which is unavoidable in the other existing robust lossless data hiding algorithm. This technique has been successfully applied to many commonly used images, thus demonstrating its generality

An Improved Reversible Data Hiding with Hierarchical Embedding for Encrypted Images and BBET

This research introduces an enhanced reversible data hiding (RDH) approach incorporating hierarchical embedding for encrypted images and employs a novel technique termed BBET (Best Bits Embedding Technique). RDH involves concealing information within a host sequence, enabling the restoration of both the host sequence and embedded data without loss from the marked sequence. While RDH has traditionally found applications in media annotation and integrity authentication, its utilisation has expanded into diverse fields. Given the rapid advancements in digital communication, computer technologies, and the Internet, ensuring information security poses a formidable challenge in safeguarding valuable data. Various reversible and stenographic techniques exist for covertly embedding or protecting data, spanning text, images, and protocols, and facilitating secure transmission to intended recipients. An influential approach in data security is reversible data hiding in encrypted images (RDHEI). This paper distinguishes between the conventional RDHEI technique, characterised by lower Peak Signal-to-Noise Ratio (PSNR) and higher Mean Squared Error (MSE), and proposes an improved RDHEI technique. As the prevalence of digital techniques for image transmission and storage rises, preserving image confidentiality, integrity, and authenticity becomes paramount. Text associated with an image, such as authentication or author information, can serve as embedded data. The recipient must adeptly recover both the concealed data and the original image. Reversible data-hiding techniques ensure the exact recovery of the original carrier after extracting the encrypted data. Classification of RDHEI techniques is based on the implemented method employed. This paper delves into a comprehensive exploration of techniques applicable to difference expansion, histogram shifting, and compression embedding for reversible data hiding. Emphasis is placed on the necessity for a reversible data-hiding technique that meticulously restores the host image. Furthermore, the study evaluates performance parameters associated with encryption processes, scrutinising their security aspects. The investigation utilises the MATLAB tool to develop the proposed BBET technique, comparing its efficacy in embedding and achieving enhanced security features. The BBET technique is characterised by reliability, high robustness, and secure data hiding, making it a valuable addition to the evolving landscape of reversible data hiding methodologies