A study on the false positive rate of Stegdetect

In this paper we analyse Stegdetect, one of the well-known image steganalysis tools, to study its false positive rate. In doing so, we process more than 40,000 images randomly downloaded from the Internet using Google images, together with 25,000 images from the ASIRRA (Animal Species Image Recognition for Restricting Access) public corpus. The aim of this study is to help digital forensic analysts, aiming to study a large number of image files during an investigation, to better understand the capabilities and the limitations of steganalysis tools like Stegdetect. The results obtained show that the rate of false positives generated by Stegdetect depends highly on the chosen sensitivity value, and it is generally quite high. This should support the forensic expert to have better interpretation in their results, and taking the false positive rates into consideration. Additionally, we have provided a detailed statistical analysis for the obtained results to study the difference in detection between selected groups, close groups and different groups of images. This method can be applied to any steganalysis tool, which gives the analyst a better understanding of the detection results, especially when he has no prior information about the false positive rate of the tool

Novel Framework for Hidden Data in the Image Page within Executable File Using Computation between Advanced Encryption Standard and Distortion Techniques

The hurried development of multimedia and internet allows for wide distribution of digital media data. It becomes much easier to edit, modify and duplicate digital information. In additional, digital document is also easy to copy and distribute, therefore it may face many threats. It became necessary to find an appropriate protection due to the significance, accuracy and sensitivity of the information. Furthermore, there is no formal method to be followed to discover a hidden data. In this paper, a new information hiding framework is presented.The proposed framework aim is implementation of framework computation between advance encryption standard (AES) and distortion technique (DT) which embeds information in image page within executable file (EXE file) to find a secure solution to cover file without change the size of cover file. The framework includes two main functions; first is the hiding of the information in the image page of EXE file, through the execution of four process (specify the cover file, specify the information file, encryption of the information, and hiding the information) and the second function is the extraction of the hiding information through three process (specify the stego file, extract the information, and decryption of the information).Comment: 6 Pages IEEE Format, International Journal of Computer Science and Information Security, IJCSIS 2009, ISSN 1947 5500, Impact Factor 0.42

A novel steganography approach for audio files

We present a novel robust and secure steganography technique to hide images into audio files aiming at increasing the carrier medium capacity. The audio files are in the standard WAV format, which is based on the LSB algorithm while images are compressed by the GMPR technique which is based on the Discrete Cosine Transform (DCT) and high frequency minimization encoding algorithm. The method involves compression-encryption of an image file by the GMPR technique followed by hiding it into audio data by appropriate bit substitution. The maximum number of bits without significant effect on audio signal for LSB audio steganography is 6 LSBs. The encrypted image bits are hidden into variable and multiple LSB layers in the proposed method. Experimental results from observed listening tests show that there is no significant difference between the stego audio reconstructed from the novel technique and the original signal. A performance evaluation has been carried out according to quality measurement criteria of Signal-to-Noise Ratio (SNR) and Peak Signal-to-Noise Ratio (PSNR)