Steganography is the art or science that is used in secret communication. It means that there is a secret message that is hidden within another cover media. The cover media may be image, video or audio and the secret message may be any type of digital message. The hidden message doesn't have any relationship with the cover media where the cover media is just to protect the secret message from hacking by unauthorized receiver. The audio cover is used in this paper because of the higher sensitivity of the human auditory system (HAS) than the human visual system (HVS). In this paper, we proposed a hybrid technique to audio steganography. This technique is based on a hybrid between two techniques of audio steganography. These techniques are Least Significant Bit (LSB) technique and modification of phase coding. The hybrid between them is for improving the performance of the phase coding where the performance of it is very low. Audio steganography performance is measured by several factors, the most important one of them is Signal to noise ratio (SNR) which is used to compare the performance of our technique with some known techniques.

Steganography is the art of amalgamating the secret message into another public message which may be text, audio or video file in a way that no one can know or imperceptible the existence of message. So, the secret message can send in a secret and obscure way using steganography techniques. In this paper, we use the audio steganography where the secret message conceal in audio file. We use audio rather than image because the human auditory system (HAS) is more sensitive than human visual system (HVS). We propose an audio steganography algorithm, for embedding text, audio or image based on Lifting Wavelet Transform (LWT) transform with modification of Least Significant Bit (LSB) technique and three random keys where these key is used to increase the robustness of the LSB technique and without it no one can know the sort of secret message type, the length of the secret message and the initial position of the embedded secret message in LSB. The performance of our algorithm is calculated using SNR and we compare the values of our proposed method with some known algorithms.