Archana A. Athawale

Information Hiding in Audio Signals

ABSTRACT Steganography is the practice of encoding secret information in indiscernible way. Audio Steganography is a technique used to transmit hidden information by modifying an audio signal in an imperceptible manner. It is mainly required for increasing security in transferring and archiving of audio files. Modern advances in computer, communication and signal Steganography complements procesrather than replaces encryption by adding another layer of security- of steganography. These advances have broadened it is much more difficult to decrypt a message if it is not known that there is a message. The basic idea of the paper is to present methods that hides information (audio, image and text) in cover audio using Least Significant Bit (LSB) coding method along with encryption so as to increase the security. Two novel methods have been proposed in this paper, one is considering parity of the digitized samples of cover audio and the other is considering the XOR operation. A novel method which is an extension to the XOR method that uses multiple LSB‟s for data embedding is also proposed. Experimental results are presented in this paper to demonstrate the effectiveness of the proposed methods. In addition, subjective listening tests are performed and the perceptual quality of the stego audio signal is found to be high.

Using assorted color spaces and pixel window sizes for colorization of grayscale images

There is no exact solution for colorization of grayscale images. In the initial work done [23], color traits transfer techniques to color grayscale images are proposed. The main focus of the techniques [23] is to minimise the human efforts needed in manually coloring the grayscale images. The human interaction is needed only to find a reference color image, then the job of transferring color traits from reference color image to grayscale image is done by proposed techniques. Here the techniques of color traits transfer to grayscale images are revisited with various color spaces as well as different sizes of pixel window. For the experimentation seven different color spaces are considered like RGB, Kekres LUV, XYZ, YIQ, YUV, YCbCr and newly proposed YCbCg. The pixel window sizes used are total twelve ranging from window with size 1x2 to 4x2. So in all 84 different versions of color traits transfer to grayscale algorithms are tested over five different images for deciding the color space and pixel window size giving best quality of coloring. The experimental results gives that the YCbCr color space gives better coloring, and the pixel window of size 3x3 suits the best in all color spaces.

Performance comparison of DCT and Walsh transform for steganography

In this paper we are introducing the concept of embedding secret message in Transform domain using low energy components using DCT and Walsh Transform. This results in less perceptible error in the stego image. The low energy components are spread over the transform domain that gives high security to the embedded message. The study is carried out for different thresholds for selecting low energy coefficients. It is observed that larger threshold value results in perceptible error in the stego image. A threshold value of 50 gives very good results so that the error in stego image is imperceptible. This also results in much higher embedding capacity then choosing the conventional middle ordered frequency elements.

Increasing the Capacity of the Cover Audio Signal by Using Multiple LSBs for Information Hiding

— Steganography is an art and science of writing hidden messages in such a way that no one apart from the intended recipient knows the existence of the message. The maximum number of bits that can be used for LSB audio steganography without causing noticeable perceptual distortion to the host audio signal is 4 LSBs, if 16 bits per sample audio sequences are used. We propose 2 novel approaches of substitution technique of audio steganography that improves the capacity of cover audio for embedding additional data. Using these methods, message bits are embedded into multiple and variable LSBs. These methods utilizes up to 7 LSBs for embedding data. Results show that both these methods improve capacity of data hiding of cover audio by 35% to 70% as compared to the standard LSB algorithm with 4 LSBs used for data embedding. From subjective listening tests, it is seen that there is no noticeable difference between the cover audio signal and the stego audio signals obtained from the proposed methods. These novel approaches for increasing capacity show better results as compared to the existing approaches.

Image retrieval using DCT on row mean, column mean and both with image fragmentation

How to search appropriate data from huge image pool has become vital issue. Because of easy availability of imaging devices, millions of images are being added to image pool every day. Image retrieval deals with searching relevant images from large image database. The paper presents novel image retrieval techniques based on discrete cosine transform applied on row mean, column mean and combination for feature extraction. Further the concept of image fragmentation is added to these to get total of 26 novel CBIR techniques. The proposed image retrieval techniques are applied to image database of 1000 images spread across 11 categories. Experimentation shows that taking row mean, column mean and combination improves the performance of image retrieval as compared to taking DCT of full image. Also fragmentation slightly helps in improving the image retrieval techniques.

Speaker identification using row mean vector of spectrogram

In this paper a simple approach to text dependent speaker identification using spectrograms and row mean is presented. This, mainly, revolves around trapping the complex patterns of variation in frequency and amplitude with time while an individual utters a given word through equalized spectrogram. These equalized spectrograms are used as a database to successfully identify the unknown individual from his/her voice. The features used for identifying, rely on optimal spectrogram segmentation and the Euclidean distance of the distributional features of the spectrograms of the unknown voice with that of a given known speaker in the database. Performance of this novel approach on a sample collected as two separate databases from 12 speakers and 28 speakers show that this methodology can be effectively used to produce a desirable success rate.

Increased capacity for information hiding using Walsh transform

Steganography is the art of passing information in a manner that the very existence of the message is unknown. The goal of steganography is to avoid drawing suspicion to the transmission of a hidden message. If suspicion is raised, then this goal is defeated. In this paper a novel method for embedding messages in an image with increased capacity is proposed. Discrete Walsh Transform is used to increase the capacity of the cover image without any perceptible change in the stego image.

Mixing Codebooks of LBG, KPE and KFCG Algorithms to Increase Capacity of Information Hiding

Many researchers have studied reversible data hiding techniques in recent years and most have proposed reversible data hiding schemes that guarantees only that the original cover image can be reconstructed completely. Once the secret data are embedded in the compression domain and the receiver wants to store the cover image in a compression mode to save storage space, the receiver must extract the secret data, reconstruct the cover image, and compress the cover image again to generate compression codes. In this paper, we propose a novel data hiding method based on VQ compressed images. Codebooks of secret message & cover images are combined using shuffle algorithm. Experimental results indicate that our proposed scheme provides 100% hiding capacity or more that means secret message can be of same or more size than cover image and better image quality compared with existing schemes based on VQ compressed images. The technique is robust against stegaanalysis technique.

Performance evaluation of image retrieval using energy compaction and imagetiling over DCT row mean and DCT column mean

Content-based image retrieval (CBIR) is a technique to retrieve images on the basis of image specific features such as colour [5, 17, 19], texture [11, 14, 16, 23] and shape [2, 4]. CBIR operates on a totally different principle from keyword indexing. Initially, features are computed for both stored and query images, and used to identify images most closely matching the query. The need to find a desired image from a collection is shared by many professional groups, including journalists, design engineers [24] and art historians. While the requirements of image users can vary considerably, it can be useful to characterize image queries into three levels of abstraction: primitive features such as colour or shape, logical features such as the identity of objects shown and abstract attributes such as the texture of image depicted [12, 15, 18]. Users needing to retrieve images from a collection come from a variety of domains, including crime prevention [13, 20], medicine, architecture [6, 9, 10, 21, 22], fashion and publishing. Many techniques have been proposed for content based image retrieval, but still there is thirst for better performance [1, 3] and faster retrieval [1, 7, 8].

Improved steganalysis of LSB matching steganography based on counting alteration rate of the number of neighbourhood gray levels

This paper proposes an improved method for attacking the LSB (Least Significant Bit) matching steganography. In LSB matching steganography the least two or more significant bit-planes of the cover image would be changed during the embedding and thus the pairs of values do not exist in stego image. In the proposed method, an image is obtained by combining the least three significant bit-planes and is divided into 3x3 overlapped subimages. The subimages are grouped into eight types, i. e. <i>T</i>_<i>1</i>, <i>T</i>_<i>2</i>, <i>T</i>_<i>3</i>, <i>T</i>_<i>4</i>, <i>T</i>_<i>5</i>, <i>T</i>_<i>6</i>, <i>T</i>_<i>7</i> and <i>T</i>_<i>8</i> according to the count of gray levels. A message is embedded by LSB matching. The alteration rate of the number of elements belonging to <i>T</i>_<i>1</i> is computed. It is found that normally the alteration rate is higher in cover image than in the corresponding stego image. This is used as the discrimination rule in the method. The literature consists of the method which focuses on the combination of least two significant bit-planes. Experimental results demonstrate that the proposed method gives better results than those obtained by combining the least two significant bit-planes. It is an efficient method to detect the LSB matching stegonagraphy in gray scale images.