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)

A Secret-Key Image Steganography Technique using Random Chain Codes

With the wide range use of digital communication technologies, the Internet has been commonly used as a channel for transmitting various images. Steganography practises have been implemented for achieving such secure transmission. The main focus of steganography is data hiding where, digital images are utilized as the cover image. One of the image steganography techniques is based on LSB method, where the secret message bits are embedded sequentially in LSB of the bytes of the carrier image. This makes the hidden message vulnerable to detection by attackers. Many secret key image steganography techniques have been developed as alternative techniques to achieve a high level of security for the hidden secret message. But, these techniques failed to use the full capacity of the carrier image. In this paper, a secret key image steganography technique has been implemented using chains of a random sequence of indices (codes) of the bytes in the carrier image. These chains have been constructed based on the secret key used. This makes the hidden message more secure and difficult to depict by attackers. Furthermore, the proposed technique uses the full capacity of the carrier image. Visual and numerical tests have been conducted for the performance of the proposed technique, the recorded results proved it can be used effectively in the field of information hiding

Robust and secure image steganography based on elliptic curve cryptography

With the ease of editing and perfect reproduction in digital multimedia, the protection of ownership and the prevention of unauthorized tampering of multimedia data (audio, image, video, and document) become important concerns . Steganography is one of these schemes that entails the opportunity of hide any secret information into images. Recently there are many techniques used for robust and secure image steganography, that can tradeoff between the capacity, payload, security, minimizing distortions of the image and high robustness. All these are challenges that need to implement a suitable technique that verify the most of these challenges. However developing a robust and secure image steganographic technique against detectability need to combined cryptography and steganography. In this paper the issue of secure and robust image data hiding is proposed through using (LSB) technique and Elliptic curve cryptography(ECC).The proposed scheme allow the sender to select a suitable cover and secret message that decidable to transmit through unsecure channel and then encrypt the message using (ECC) and embed it by (LSB) into selected cove

Data Hiding Based on Intelligent Optimized Edges for Secure Multimedia Communication

Recently, image steganography has received a lot of attention as it enables for secure multimedia communication. Payload capacity and stego image imperceptibility are a critical factors of any steganographic technique. In order to receive maximum embedding capacity with a minimum degradation of stego images, secret data should be embedded carefully in a specific regions. In this paper, data hiding is considered as an optimization problem related to achieving optimum embedding level of the cover image. Embedding data in edge area provide high imperceptibility. However, the embedding capacity of edge region is very limited. The work attempt to improve the edge based steganography by incorporates edge detection and vision science research. Genetic Algorithm that uses human visual system characteristics approach for data hiding is presented. Primarily, the approach applies Differences of Gaussian detector which closely resembles the human visual behavior. Secondly, the edge profusion indicates the level of threshold visibility with the help of Genetic Algorithm training. The suggested solution uses Contrast Sensitivity Function (CSF) which produces the edges based on the size of the embedding information. The authors of this paper compared their technique with other classical and recent works. The quality of the steganography is measured based on various quality metrics such as PSNR, wPSNR, SSIM and UIQI. These metrics declare the stability between imperceptibility and large embedding capacit