Steganography Techniques

CHAPTER 3

LITERATURE REVIEW

3.1 INTRODUCTION

This chapter analyses the research relevant of steganographic and steganalysis techniques available for secret sharing. Secret sharing plays major role in many applications such as military application, network communication, wireless applications, etc. There are many techniques proposed by different authors in order to share the information between the two parties and to provide a secured communication. The following sections discuss the existing techniques for secret sharing in cryptography and steganography. Various steganography techniques and overview of different types of image steganography methods are discussed in section 3.2 and in section 3.3. The reviews and highlights of the

In Greek steganography this is called as “covered writing”, which is the science of communication using hidden information. To analyze the existing techniques this method is introduced. This technique embeds and extracts the hidden information of large length inside digital images which maintains the range and size of the original image. Without the knowledge of the original image the hidden message can be recovered using the suitable keys. Methods related to speed spectrum like image restoration and error control methods are explained and the presentation of the system is showed. A message fixed by this method sometimes occurs in the form such as text, imagery, or any digital signal. Applications for that data-hiding scheme contains in-band captioning, covert communication, image tamper proofing, authentication, embedded control, and revision tracking. It shows a totally secure steganographic

Here the number of revising points are calculated which introduce the pulse distortion in the histogram. The histogram shows the complete differences of the pixel pairs. With this study, the goal of steganalytic technique based on B-Spline fitting is planned. The leading presentation of this research contrasted with the blind steganalyzer. This method calculated the accurate threshold values of message embedding process. And it split the entire message block of the stego image into number of unit blocks.

Trivedi et al (2005) proposed a method in which the exact key value is identified by analyzing the difference between the stego sequences and the shifted sequence on the embedding path. The consecutive features like time, spatial, or frequency domain are used to hidden message of a host signal where embedding algorithms class is described by sequential steganography. This will overcome the difficulty of finding the key values using the hypothesis testing. This method is simple and quicker than the hypothesis