Least significant bit matching steganalysis based on feature analysis

Steganography is a science of hiding messages into multimedia documents. In steganography, there is a technique in which the least significant bit is modified to hide the secret message, known as the least significant bit (LSB) steganography. Several steganalyzers are developed to detect least significant bit (LSB) matching steganography. Least significant bit matching images are still not well detected, especially, at low embedding rate. In this paper, we have improved the least significant bit steganalyzers by analyzing and manipulating the features of some existing least significant bit matching steganalysis techniques. A comprehensive set of experiments is carried out to justify proposed method´s applicability and evaluate its performance against the existing least significant bit matching steganalysis techniques.