Audio Watermarking Techniques

Audio watermarking is a method that embeds inaudible information into digital audio data. This paper describes an audio watermarking scheme using the Least Significant Bit (LSB) in the multiresolution domain exploiting the perceptual evaluation of audio quality algorithm (PEAQ) and MP3 compression characteristics. To guarantee perfect inaudibility propriety, we adapt the PEAQ algorithm to select the adequate audio band used to hide the watermark in the LSB of the multiresolution coefficients. Additionally, we use some MP3 compression characteristics to increase robustness of the scheme and we duplicate the watermark bits in the whole audio signal blocks assuring then an important ratio property without affecting the inaudibility property. The described method provides good robustness results against compression and StirMark attacks. Besides, it allows blind retrieval of embedded watermark which does not need the original audio.

The article covers a brief summary of modern approaches for embedding additional data in audio signals. It could have many causes - for the purposes of access control or identification related to particular type of audio. This top-secret information is not "visible" for a user. The leading determination for watermarking by audio is to defend beside probable extortions in the audio records and for copyright harm or illegal altering; reality for such information can be unsure by audio watermarking. Steganography and cryptography are two techniques these techniques are related in the manner that they together are used to safeguard private facts. There is lack in characteristic of original image we recommend a generalized form of Reversible Contrast Mapping (RCM) is an in complex integer transform that applies to pairs of pixels. For image watermarking Contrast mapping is invertible procedure, because least significant bits (LSBs) of the transformed pixels are forfeit. The data space occupied by the LSBs is expedient for information hiding. The embedded information bit-rates of reversible watermarking structure are highest bit-rates till date. The system does not need further records compression, and, in terms of mathematical complexity, it is having lowest complexity. Also robustness against cropping can be guaranteed.

The research objective is to hide messages through images using the LSB (Least Significant Bit) method and Caesar Chipper and Rivest Code 4 encryption. The LSB (Least Significant Bit) method is used as a message hiding technique in steganography where hiding hidden messages is done by changing a few bits in the segment. image with a secret message. The results of this study resulted in an implementation using the Least Significant Bit (LSB) to be applied to institutions with an interest in maintaining the confidentiality of encrypted image output, changing the image file size and sound (audio) file size.

Spatial LSB±1 steganography changes smooth characteristics between adjoining pixels of the raw image. We present a novel steganalysis method for LSB±1 steganography based on feature vectors derived from the co-occurrence matrix in the spatial domain. We investigate how LSB±1 steganography affects the bit planes of an image and show that it changes more least significant bit (LSB) planes of it. The co-occurrence matrix is derived from an image in which some of its most significant bit planes are clipped. By this preprocessing, in addition to reducing the dimensions of the feature vector, the effects of embedding were also preserved. We compute the co-occurrence matrix in different directions and with different dependency and use the elements of the resulting co-occurrence matrix as features. This method is sensitive to the data embedding process. We use a Fisher linear discrimination (FLD) classifier and test our algorithm on different databases and embedding rates. We compare our scheme with the current LSB±1 steganalysis methods. It is shown that the proposed scheme outperforms the state-of-the-art methods in detecting the LSB±1 steganographic method for grayscale images.

In recent years, internet revolution resulted in an explosive growth in multimedia applications. The rapid advancement of internet has made it easier to send the data/image accurate and faster to the destination. Besides this, it is easier to modify and misuse the valuable information through hacking at the same time. Digital watermarking is one of the proposed solutions for copyright protection of multimedia data. A watermark is a form, image or text that is impressed onto paper, which provides evidence of its authenticity. In this paper an invisible watermarking technique (least significant bit) and a visible watermarking technique is implemented. This paper presents the general overview of image watermarking and different security issues. Various attacks are also performed on watermarked images and their impact on quality of images is also studied. In this paper, Image Watermarking using Least Significant Bit (LSB) algorithm has been used for embedding the message/logo into the image. This work has been implemented through MATLAB. Keywords - Watermarking, Least Significant Bit (LSB), JPEG (Joint Photographic Experts Group), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR).

In this paper, the spread spectrum watermarking in wavelet domain is optimised by using a number of techniques to make it more efficient when executed by a platform running on mobile devices. The proposed techniques can be executed efficiently and consume less computational and power resources as compared to the conventional spread spectrum-based watermarking. The proposed technique represents binary bits in the watermark using symbols, wherein each symbol represents at least 2 binary bits. A symbol is then mapped into a pseudo noise sequence and embedded in the digital image. Our analytical results show that our schemes reduce the number of operations required for watermarking by ∼50%, while our experimental results show that our schemes save about ∼59 and ∼67% in processing time and energy consumption, respectively.

There is a huge resource of data available on the internet which one can access without realizing that the person is even authorized to access it or not. The hard work of the original resource person can easily be compromised. Digital watermarking is an answer to overcome this issue. This paper introduces a hybrid of LSB and DCT techniques, LSB(Least Significant Bit) and DCT(Discrete Cosine Transformation). The paper studies the two techniques along with the proposed technique and a comparison is drawn between the three based on MSE and PSNR values obtained. The introduced hybrid technique performs better in comparison to DCT and LSB. The MSE calculated was 64% better than LSB and 60% better than DCT resultantly PSNR is also observed to be better than LSB and DCT.

We investigate the application of distributed source coding to a single-channel speech or audio signal. We compare two methods. In the first, we encode signal sequences using low-density parity check codes in an approach that resembles methods used in video coding. In the second, we encode each sample with only a set of least significant bits (LSB) of the quantization index. In both methods the parameters of a statistical signal model are estimated at the encoder and transmitted to the decoder. The signal model is used only at the decoder. Our results indicate that the LSB coding method is more effective. We show that the order-k entropy of a sequence of LSBs converges more quickly to the entropy rate of the scalar quantized signal than the order-k entropy of the quantized signal itself. As a result, we can approach the rate-distortion bound by applying entropy coding to successive short (several samples) segments of the sequence of LSB sample. The LSB coding method can be extended to lattice quantization.

When files are created, there are always bits that are not really needed and are not at least important. These bits have the capability of being changed with the information which must be hidden in the file, without damage and changes in the file. There are different methods of image steganography, among which Least Significant Bit (LSB) method is the most common one and we intend to use this method for making stego image. A LSB replacement-based newly developed method (the least significant bit) has been presented in 24 bit color images. We propose a newly developed method of information security in RGB color images using a combined method composed of a two-component method based on the replacement and adaptation of LSB for hiding information and providing more security level. We have used Advanced Encryption Standard (AES) for resisting against attacks, a combined filtering and different disorders.

The sending of encrypted messages attracts the attention of programmers and crackers who would seek to intercept and uncover the messages before arrive their intended destination. Steganography is one way to mask communication by hiding unrevealed message inside another unsuspecting message. Steganography can be combined with cryptography in order to offer a satisfactory measure of privacy and security. In this study, a new approach of the least significant bit steganography has been proposed which improves on the 1 byte least significance technique. A detail description of image steganography procedures based on Least Significant Bit (LSB) to reduce the possibility of a message being recognized is provided. It includes steganalysis - the techniques by which secret information is been extracted.

Security of information is becoming main criteria while transferring information through communication networks. Nowadays images are used as information source; therefore its security from unauthorized or unintended access is important. Image encryption play an important role in protecting images from hacking and stealing while sending over an unsecured channel. The proposed method is a combination of encryption using Hill cipher algorithm along with Elliptic curve for enhanced security. Elliptic curve cryptographic method is used to make the system to asymmetric from the less secured symmetric key encryption technique; hill cipher algorithm. In our proposed method we use both grayscale images as well as color images regardless its size. Steganography of actual image with a cover image before encryption is an advantage. The cover image is selected as it mocks like an informative to unauthorized access. Least Significant Bit (LSB) steganography method is used here as it provides more security than any other methods.

Background and Objective: The public and group communication carried out in the social, cloud, and mobile networks suffer from unauthorized users. The data security is required for secure authentication, monetary transactions and other sensitive information. The steganography methods empower the user with invulnerable communication in public domain. In this paper, a region secure and pattern based alternate 2B-3C (2Bit-3Channel) Steganography method is proposed to improve the content reliability and data security. Methods: In this method, the cover pixels are retrieved by applying the spiral rectangular pattern over the cover image. This spiral pattern also secures the core content region and the pixels from the core ROI (Region of Interest) is used as a cover only for larger size secret information. In this proposed steganography method, two channels are considered alternatively based on the defined rules. The LSB (Least Significant Bit) of both channels is XOR with input data bits and key to perform data hiding. The method is applied on real time color images taken from COREL and USC-SIPI-ID. The evaluation of proposed steganography approach is done using MSE (Mean Square Error), PSNR (Peak Signal-to-Noise Ratio), BER (Bit Error Rate), NCC (Normalized Cross Correlation) and SSIM (Structural Similarity Index Matrix). Result: The comparative results are generated for 50 real time images against the existing LSB (Least Significant Bit), LSBM (Least Significant Bit Modulation), LSBMR (Least Significant bit Matched Revisited), SCC (Stego Color Cycle), SHSI (Simple Hue-Saturation-Intensity), HIS-MLSB(Simple Hue-Saturation-Intensity-Modified LSB) and IMMEA(Iterative Magic Matrix Encryption Algorithm) methods. Conclusion: The experimentation results verified that the proposed 2B-3C approach improved the data hiding in qualitative and quantitative aspects.

Addition of hash component in a message is always for verification of authentication of message without integrity. In order to retain integrity certain schemes such as Merkle–Damgard scheme or Rabin scheme based on the block cipher can be used. However, the block cipher schemes in messages do not get applicable on image which are encoding message in a visual format. Therefore, block cipher based schemes are not able to provide tamper localization in case of image authentication. Tamper detection is needed in case of images as it is not visualized without proper verification. Moreover, localization is not possible by hash verification making the authentication processes only detectable but not identifiable. The paper presents a generation process of three least significant bits of hash function. The image insertion is not visualized due to human eye limitation. The method proposed is able to embed a secret image (gray scale) inside a corner image. Experimental results show an improvement in peak signal-to-noise ratio (PSNR) values of the proposed technique over the other techniques available, such as hash-based LSB(2-3-3) image steganography in spatial domain. This paper proposes an image authentication process not only for robustness, security, and tamper detection but also successfully able to identify tamper by a process of tamper localization. The parameters compared include the classical mechanism along with newly introduced entropy measurement of images. A performance analysis is able to show the result claimed in the paper. The paper uses a least significant bit (LSB) based hash function, which is a blind technique as image-related information is never sent to receiver separately. In fact, the proposed approach is a clever design as the generated hash function will be embedded in the image itself. The proposed mechanism is able to offer good imperceptibility between original image and embedded image with hash bits. Even a minute tampering can be detected with proper localization; the localization of tampering is having its wide applicability in case of forensic evidence of malicious image morphing.

This paper introduces a best approach for Least Significant Bit (LSB) based on image steganography that enhances the existing LSB substitution techniques to improve the security level of hidden information. It is a new approach to substitute LSB of RGB true color image. The new security conception hides secret information within the LSB of image where a secret key encrypts the hidden information to protect it from unauthorized users. In general, in LSB methods, hidden information is stored into a specific position of LSB of image. For this reason, knowing the retrieval methods, anyone can extract the hidden information. In our paper, hidden information is stored into different position of LSB of image depending on the secret key. As a result, it is difficult to extract the hidden information knowing the retrieval methods. We have used the Peak Signal-to-Noise Ratio (PSNR) to measure the quality of the stego images. The value of PSNR gives better result because our proposed method changes very small number of bits of the image. The obtained results show that the proposed method results in LSB based image steganography using secret key which provides good security issue and PSNR value than general LSB based image steganography methods.

With the development of depth data acquisition technologies, access to high-precision depth with more than 8-b depths has become much easier and determining how to efficiently represent and compress high-precision depth is essential for practical depth storage and transmission systems. In this paper, we propose a layered high-precision depth compression framework based on an 8-b image/video encoder to achieve efficient compression with low complexity. Within this framework, considering the characteristics of the high-precision depth, a depth map is partitioned into two layers: 1) the most significant bits (MSBs) layer and 2) the least significant bits (LSBs) layer. The MSBs layer provides rough depth value distribution, while the LSBs layer records the details of the depth value variation. For the MSBs layer, an error-controllable pixel domain encoding scheme is proposed to exploit the data correlation of the general depth information with sharp edges and to guarantee the data format of LSBs layer is 8 b after taking the quantization error from MSBs layer. For the LSBs layer, standard 8-b image/video codec is leveraged to perform the compression. The experimental results demonstrate that the proposed coding scheme can achieve real-time depth compression with satisfactory reconstruction quality. Moreover, the compressed depth data generated from this scheme can achieve better performance in view synthesis and gesture recognition applications compared with the conventional coding schemes because of the error control algorithm.