Steganography in audio files – COTS software analysis

The paper presents the analysis of the Commercial Off-The-Shelf (COTS) software regarding the ability to be used in audio steganography techniques. Such methods are a relatively new tool for hiding and transmitting crucial information, also being used by hackers. In the following work, the publicly available software dedicated to audio steganography is examined. The aim was to provide the general operating model of the information processing in the steganographic effort. The embedding method was analyzed for each application, providing interesting insights and allowing classifying the methods.The results prove that it is possible to detect the hidden message within the specific audio file and identify the technique that was used to create it. This may be exploited further during the hacking attack detection and prevention

Improved steganalysis technique based on least significant bit using artificial neural network for MP3 files

MP3 files are one of the most widely used digital audio formats that provide a high compression ratio with reliable quality. Their widespread use has resulted in MP3 audio files becoming excellent covers to carry hidden information in audio steganography on the Internet. Emerging interest in uncovering such hidden information has opened up a field of research called steganalysis that looked at the detection of hidden messages in a specific media. Unfortunately, the detection accuracy in steganalysis is affected by bit rates, sampling rate of the data type, compression rates, file track size and standard, as well as benchmark dataset of the MP3 files. This thesis thus proposed an effective technique to steganalysis of MP3 audio files by deriving a combination of features from MP3 file properties. Several trials were run in selecting relevant features of MP3 files like the total harmony distortion, power spectrum density, and peak signal-to-noise ratio (PSNR) for investigating the correlation between different channels of MP3 signals. The least significant bit (LSB) technique was used in the detection of embedded secret files in stego-objects. This involved reading the stego-objects for statistical evaluation for possible points of secret messages and classifying these points into either high or low tendencies for containing secret messages. Feed Forward Neural Network with 3 layers and traingdx function with an activation function for each layer were also used. The network vector contains information about all features, and is used to create a network for the given learning process. Finally, an evaluation process involving the ANN test that compared the results with previous techniques, was performed. A 97.92% accuracy rate was recorded when detecting MP3 files under 96 kbps compression. These experimental results showed that the proposed approach was effective in detecting embedded information in MP3 files. It demonstrated significant improvement in detection accuracy at low embedding rates compared with previous work

Steganalysis of Hydan

Hydan is a steganographic tool which can be used to hide any kind of information inside executable files. In this work, we present an efficient distinguisher for it: We have developed a system that is able to detect executable files with embedded information through Hydan. Our system uses statistical analysis of instruction set distribution to distinguish between files with no hidden information and files that have been modified with Hydan. We have tested our algorithm against a mix of clean and stego-executable files. The proposed distinguisher is able to tell apart these files with a 0 ratio of false positives and negatives, thus detecting all files with hidden information through Hydan

Steganography integration into a low-bit rate speech codec

Low bit-rate speech codecs have been widely used in audio communications like VoIP and mobile communications, so that steganography in low bit-rate audio streams would have broad applications in practice. In this paper, the authors propose a new algorithm for steganography in low bit-rate VoIP audio streams by integrating information hiding into the process of speech encoding. The proposed algorithm performs data embedding while pitch period prediction is conducted during low bit-rate speech encoding, thus maintaining synchronization between information hiding and speech encoding. The steganography algorithm can achieve high quality of speech and prevent detection of steganalysis, but also has great compatibility with a standard low bit-rate speech codec without causing further delay by data embedding and extraction. Testing shows, with the proposed algorithm, the data embedding rate of the secret message can attain 4 bits / frame (133.3 bits / second)

Code wars: steganography, signals intelligence, and terrorism

This paper describes and discusses the process of secret communication known as steganography. The argument advanced here is that terrorists are unlikely to be employing digital steganography to facilitate secret intra-group communication as has been claimed. This is because terrorist use of digital steganography is both technically and operationally implausible. The position adopted in this paper is that terrorists are likely to employ low-tech steganography such as semagrams and null ciphers instead