A new data embedding method for mpeg layer III audio steganography

A new method of MP3 steganography is proposed with emphasis on increasing the steganography capacity of the carrier medium. This paper proposes a data embedding algorithm to hide more information for compressed bitstream of MP3 audio files. The sign bits of Huffman codes are selected as the stego-object according to the Huffman coding characteristic in region of Count1. Embedding process does not require the main MP3 audio file during the extraction of hidden message and the size of MP3 file cannot be changed in this step. Our proposed method caused much higher information embedding capacity with lower computational complexity compared with MP3Stego tools. Experimental results show an excellent imperceptibility for the new algorithm

Lossy Distortion as a Musical Effect

73 pagesLossy audio compression is a digital process that uses models of human hearing to remove parts of the sound deemed less important, in order to compress audio to much smaller file sizes. The MP3 encoding process, one of the most famous lossy audio compression formats, can impart audio with a distinctive watery, muffled sound at higher levels of compression. This sound, which I call “lossy distortion,” can be used as a musical effect to inspire nostalgia for early digital audio, or for a more abstract, ethereal sound. In analyzing creative uses of lossy distortion and existing plugins for lossy distortion, I identify some desirable features that are lacking from existing plugins. To fill these gaps, I built two lossy distortion plugins. One, called Empy, gives the user control over a wide variety of lossy distortion sounds. The other, Fish, emulates a particular sound of lossy distortion that other plugins struggle to achieve, by modifying a popular piece of MP3 encoding software. In their sound and user interface, these plugins explore new ground in the rapidly developing field of lossy distortion plugins

Improved steganalysis technique based on least significant bit using artificial neural network for MP3 files

MP3 files are one of the most widely used digital audio formats that provide a high compression ratio with reliable quality. Their widespread use has resulted in MP3 audio files becoming excellent covers to carry hidden information in audio steganography on the Internet. Emerging interest in uncovering such hidden information has opened up a field of research called steganalysis that looked at the detection of hidden messages in a specific media. Unfortunately, the detection accuracy in steganalysis is affected by bit rates, sampling rate of the data type, compression rates, file track size and standard, as well as benchmark dataset of the MP3 files. This thesis thus proposed an effective technique to steganalysis of MP3 audio files by deriving a combination of features from MP3 file properties. Several trials were run in selecting relevant features of MP3 files like the total harmony distortion, power spectrum density, and peak signal-to-noise ratio (PSNR) for investigating the correlation between different channels of MP3 signals. The least significant bit (LSB) technique was used in the detection of embedded secret files in stego-objects. This involved reading the stego-objects for statistical evaluation for possible points of secret messages and classifying these points into either high or low tendencies for containing secret messages. Feed Forward Neural Network with 3 layers and traingdx function with an activation function for each layer were also used. The network vector contains information about all features, and is used to create a network for the given learning process. Finally, an evaluation process involving the ANN test that compared the results with previous techniques, was performed. A 97.92% accuracy rate was recorded when detecting MP3 files under 96 kbps compression. These experimental results showed that the proposed approach was effective in detecting embedded information in MP3 files. It demonstrated significant improvement in detection accuracy at low embedding rates compared with previous work

Subjective Evaluation of Audiovisual Signals

This paper deals with subjective evaluation of audiovisual signals, with emphasis on the interaction between acoustic and visual quality. The subjective test is realized by a simple rating method. The audiovisual signal used in this test is a combination of images compressed by JPEG compression codec and sound samples compressed by MPEG-1 Layer III. Images and sounds have various contents. It simulates a real situation when the subject listens to compressed music and watches compressed pictures without the access to original, i.e. uncompressed signals

High capacity data embedding schemes for digital media

High capacity image data hiding methods and robust high capacity digital audio watermarking algorithms are studied in this thesis. The main results of this work are the development of novel algorithms with state-of-the-art performance, high capacity and transparency for image data hiding and robustness, high capacity and low distortion for audio watermarking.En esta tesis se estudian y proponen diversos métodos de data hiding de imágenes y watermarking de audio de alta capacidad. Los principales resultados de este trabajo consisten en la publicación de varios algoritmos novedosos con rendimiento a la altura de los mejores métodos del estado del arte, alta capacidad y transparencia, en el caso de data hiding de imágenes, y robustez, alta capacidad y baja distorsión para el watermarking de audio.En aquesta tesi s'estudien i es proposen diversos mètodes de data hiding d'imatges i watermarking d'àudio d'alta capacitat. Els resultats principals d'aquest treball consisteixen en la publicació de diversos algorismes nous amb rendiment a l'alçada dels millors mètodes de l'estat de l'art, alta capacitat i transparència, en el cas de data hiding d'imatges, i robustesa, alta capacitat i baixa distorsió per al watermarking d'àudio.Societat de la informació i el coneixemen