Abstract:
Internet has emerged a major platform to support many activities in our daily life. However, the
countless facilities offered by Internet brings numerous challenges thereof. One of the major
challenge is regarding security and privacy of data transmitted over internet. Information security
is an emerging area of research, in which steganography is a promising technique to hide the
presence of secret information into the cover media such as, image, video, audio files. Although
various steganographic schemes have been designed and proposed by researchers, however, the
tradeoff among important steganography parameters, i.e., embedding capacity and Peak Signal to
Noise Ratio (PSNR) remains challenging, because efforts to enhance the embedding capacity
significantly degrades the PSNR and vice versa. Since, both these parameters have an important
impact over the steganographic scheme therefore, a compromise on anyone may jeopardize the
desired objectives. Hence this research fill-up this gap by proposing a novel steganographic
framework that ensures an optimal tradeoff between embedding capacity and PSNR by achieving
higher embedding capacity with lower visual quality distortions (PSNR), while comparing with
current state of the art approaches. The proposed scheme uses Pixel Value Difference (PVD), Least
Significant bits (LSB) and Difference Expansion (DE) techniques simultaneously and hide the
secret data in the cover image with due emphasis on achieving higher embedding capacity, as well
as, visual quality. The validity of proposed framework has been demonstrated using benchmark
case study by choosing test images from publicly available Signal and Image Processing Institute
(SIPI) dataset. The achieved results prove that the proposed scheme, enhances the embedding
capacity by 1053858 bits (min) to 1061248 bits (max) (on average 0.27% to 0.63% more than the
reported so far), while maintaining the visual quality within 32dB (min) - 36dB (max) (on average
1.69 to 5.21 dB improvement). Moreover, because of higher PSNR, our proposed scheme is more
effective against histograms and statistical attacks due to improved visual quality of the stego
images
