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 Survey on Image Steganography & its Techniques in Spatial & Frequency Domain

Steganography is an intelligent art of communicating in a way which hides the endurance of the communication. The image steganography technique takes the asset of confined power of visual system of human being. The art of hiding information such that it averts ferreting out of hidden messages is getting very popular nowadays, which is referred as Steganography. The word Steganography has been educed from the two Greek words - Steganos, which mean covered or secret and Graphy mean writing or drawing. There have been many techniques for hiding information or messages in images in such a manner that the modifications made to the image are perceptually undetected. This paper proposes the evaluation of a few techniques of the Image Steganography in spatial domain and frequency domain. The Image Steganography techniques in spatial domain that would be discussed are Least-Significant-Bit (LSB), LSB Replacement, LSB Matching, and Bit Plane Complexity Segmentation Steganography and frequency domain techniques to be conferred in this paper are Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), Discrete Fourier Transform (DFT) and Singular Valued Decomposition (SVD). Steganography technique is intended to be compared with the Watermarking Technique. DOI: 10.17762/ijritcc2321-8169.15027

Hiding data in images using steganography techniques with compression algorithms

Steganography is the science and art of secret communication between two sides that attempt to hide the content of the message. It is the science of embedding information into the cover image without causing a loss in the cover image after embedding.Steganography is the art and technology of writing hidden messages in such a manner that no person, apart from the sender and supposed recipient, suspects the lifestyles of the message. It is gaining huge attention these days as it does now not attract attention to its information's existence. In this paper, a comparison of two different techniques is given. The first technique used Least Significant Bit (LSB) with no encryption and no compression. In the second technique, the secret message is encrypted first then LSB technique is applied. Moreover, Discrete Cosine Transform (DCT) is used to transform the image into the frequency domain. The LSB algorithm is implemented in spatial domain in which the payload bits are inserted into the least significant bits of cover image to develop the stego-image while DCT algorithm is implemented in frequency domain in which the stego-image is transformed from spatial domain to the frequency domain and the payload bits are inserted into the frequency components of the cover image.The performance of these two techniques is evaluated on the basis of the parameters MSE and PSNR

Text Hiding in Coded Image Based on Quantization Level Modification and Chaotic Function

A text hiding method in codded image is presented in this paper that based on quantization level modification. The used image is transformed into wavelet domain by DWT and coefficient of transform is partitioned into predefined block size. Specific threshold has been used to classify these blocks into two types named smooth and complex. Each type has its own method of text hiding (binary data), for smooth blocks, secret bits which represent the text data are switched by the bitmap. In order to reduce distortion, the quantization levels are modified. To reach extra embedding payload the quantization level could carry extra two bits depending on other threshold. The complex block carry one data bit on each block and quantization levels are swapped to reduce distortion with bitmap flipping. The proposed method result shows a high signal to noise ratio, with studying capacity as important in this work

LWT based encrypted payload steganography

Steganography is used in covert communication for transportation of secrete information. In this paper we propose LWT based Encrypted Payload Steganography (LEPS). The payload is segmented into two parts say block 1 and block 2. The LWT is applied on block 2 to generate four sub bands. Payload block 1 is retained in the spatial domain itself. The values of approximation band coefficients of block 2 and spatial domain intensity values of block 1 are compressed. The LWT is applied on cover image to generate wavelet sub bands and considered only diagonal sub bands (XD). The XD band is decomposed into three parts. The key values are embedded into first part of XD band. The compressed payload is embedded in second and third blocks of XD adaptively. The payload can be retrieved at the destination by adapting reverse process of embedding. It is observed that the values of PSNR and capacity are better in the case of proposed algorithm compared to existing algorithm

Integration of biometrics and steganography: A comprehensive review

The use of an individual’s biometric characteristics to advance authentication and verification technology beyond the current dependence on passwords has been the subject of extensive research for some time. Since such physical characteristics cannot be hidden from the public eye, the security of digitised biometric data becomes paramount to avoid the risk of substitution or replay attacks. Biometric systems have readily embraced cryptography to encrypt the data extracted from the scanning of anatomical features. Significant amounts of research have also gone into the integration of biometrics with steganography to add a layer to the defence-in-depth security model, and this has the potential to augment both access control parameters and the secure transmission of sensitive biometric data. However, despite these efforts, the amalgamation of biometric and steganographic methods has failed to transition from the research lab into real-world applications. In light of this review of both academic and industry literature, we suggest that future research should focus on identifying an acceptable level steganographic embedding for biometric applications, securing exchange of steganography keys, identifying and address legal implications, and developing industry standards

Security System for Safe Transmission of Medical Images

This paper develops an optimised embedding of payload in medical images by using genetic optimisation. The goal is to preserve the region of interest from being distorted because of the watermark. By using this system there is no need to manually define the region of interest by experts as the system will apply the genetic optimisation to select the parts of image that can carry the watermark guaranteeing less distortion. The experimental results assure that genetic based optimisation is useful for performing steganography with less mean square error percentage