الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
The recent revolution of the Internet as a collaborative medium has opened the door for people who want to share their work. Nevertheless, this may cause serious problems for privacy and copyright protection. Steganography is a powerful tool for protecting important data during transmission. It’s used to hide any secret information like text, image or audio behind a cover file. In this thesis, some new computationally effective steganographic techniques have been proposed to achieve high embedding rate and robustness under the perceptual transparency restrictions for uncompressed audio. The first approach presented an efficient steganography scheme based on sample comparison in Wavelet Domain, where secret image is firstly encrypted using RSA algorithm, then these encrypted values are hidden in selected coefficients of audio Wavelet Coefficients according to Pseudo Random Sequence. selected coefficients are changed by a threshold value depending on the encrypted image bits. The second approach exhibited a modified robust audio steganography scheme using integer wavelet transform and logistic maps random sequence generation. The strength of the algorithm comes from its simplicity and full recovery of hidden data using integer wavelet. The algorithm also provided robust encryption using chaotic maps hopping technique. The third technique proposed an efficient secure algorithm depending on the high correlation between successive audio samples to hide image data in the small differences between successive samples, so it provides higher hiding capacity with lower distortion in the audio signal. Furthermore, the performance of audio steganography using low and medium bitrate speech streams was studied and a simple and robust algorithm was presented by using adopted LSB technique in hiding data in CELP parameters of coded speech with a specified chaotic maps sequence quality. On the other hand, a new technique for image hiding in high bitrate audio files was presented. The intended method depended on hiding data within silent intervals of audio signals by modifying their sample values according to small threshold without a great effect on the quality of audio signal. The silent intervals were extracted using two simple and effective features, namely signal energy and spectral centroid. The proposed technique has high transparency, robustness and inaudibility. Stereo audio signals were also investigated and used in hiding information in two approaches. The first approach compared the performance of image hiding methods in stereo audio signals using two different wavelet transform types, which are discrete wavelet types which are discrete wavelet transform (DWT) and Integer wavelet transform (IWT). The suitable applications for each algorithm were also presented. Lastly, the second approach which used stereo audio signal has adopted a new method using Complete Complementary Codes to encode color images and hide two versions of it in the two channels of stereo audio signals. To conclude, Extensive experiments are carried out to evaluate and compare the proposed schemes with the state of the art schemes, and the results of all the above mentioned novel approaches included in this thesis have been empirically validated as to indicate their utility and value. The results revealed that our methods achieve good robustness and imperceptibility.