Scope of Support Vector Machine in Steganography

Abstract

Steganography is a technique used for secure transmission of data. Using audio as a cover file opens path for many extra features. In order to overcome the limitations of conventional LSB technique, various variants were proposed by different authors. In order to achieve robustness, use of various optimization techniques has been tradition. In this paper the focus is put on use of Genetic Algorithm and Particle Swarm Intelligence in steganography. To list detailed scope, merits and de-merits of the two optimization techniques is the main constituent of this paper. In spite of analyzing the two techniques, the motivation and applicability of machine learning algorithm in the problem statement is also discussed. This paper will guide the path in using Support Vector Machine for optimizing the data hiding.