Audio Steganography Analysis Techniques

Steganography, as a part of data hiding, is the art and science of hiding the very presence of communication by embedding secret messages into innocent looking electronic signals such as digital images, video and audio. To achieve covert communication, stego-signals, signals containing any secret messages, should be indistinguishable from cover-signals, signals not containing any secret messages. If suspicion is raised, then this goal is defeated. In this respect, steganalysis is the set of techniques that aim to distinguish between cover-signals and stego-signals. With a vast number of publicly available steganographic tools on the internet, the danger of their misuse has recently created a pressing need for detection of steganography, so the research on steganalysis is important.Audio steganography is gaining widespread importance. In this paper, we address the steganalysis of digital audio signals. The main research works are as follows:(1) This paper describes the principle characteristics and current research status of steganography and steganalysis, discusses the algorithms of audio steganography and steganalysis, and identifies characteristics in current steganography software.(2) Three detection algorithms which are aimed at LSB steganography algorithm, Chi-Square test, RS test and Sampe Pair Analysis have been tested on audios. The three discrimination function tests are analyzed from both principle and experiment results. Results show that the image LSB steganalysis ways can be used for audio steganalysis. And this paper proposes an extension of Chi-Square test method.(3) Based on the idea that any steganographic technique will invariably perturb the statistics of the cover signal to some extent, this paper gives three universal steganalysis techniques: Steganalysis based on Short-time Fourier Transform and Neural Networks, the higher order coefficient detection based on Support Vector Machine, steganalysis of audio based on quality metrics. The three techniques give different results, but all show that they are effective, can be used to detect the presence of hidden messages in audio. The advantage and disadvantage of universal steganalysis are also discussed.(4) Finally, this paper points out some further research directions of steganalysis.