Steganography is the art and science of hiding the presence of conmunication by embedding secret message into digital images. The steganographic techniques can be applied in many areas. On one hand, people can benefit from their application. For example, they can be used for copyright protection. On the other hand, these techniques may be used by criminals or terrorists for malicious purposes. For example, terrorists may use the techniques to transmit the secret plan of terror attacks. Law enforcement and security authorities have concerns about such activities. It is necessary to devise the methods to detect steganographic systems. The detection of steganography belongs to the field of steganalysis.

Steganalysis is the art and science of detecting embedded message based on visual inspection, statistical analysis or other methods. Steganalysis detection methods can be classified into two categories: specific and general detection. The specific detection methods deal with the targeted steganographic systems, while the general detection methods provide detection regardless of what the steganographic systems are.

The typical detection methods are reviewed and studied in this thesis. In addition, a general detection based on artificial neural network is proposed. The performance of this detection method on detecting a generic quantization index modulation (QIM) technique is presented.