Quantitative Structural Steganalysis of Jsteg
نویسندگان
چکیده
منابع مشابه
JSteg: Steganography and Steganalysis
1.Introduction: Steganography is the art and science of hiding communication; a steganographic system thus embeds hidden content in unremarkable cover media so as not to arouse an eavesdropper’s suspicion. In the past, people used hidden tattoos or invisible ink to convey steganographic content. Today, computer and network technologies provide easy-to-use communication channels for steganograph...
متن کاملOn the Performance of Wavelet Decomposition Steganalysis with JSteg Steganography
In this paper, we study the wavelet decomposition based steganalysis technique due to Lyu and Farid. Specifically we focus on its performance with JSteg steganograpy. It has been claimed that the LyuFarid technique can defeat JSteg; we confirm this using different images for the training and test sets of the SVM classifier. We also show that the technique heavily depends on the characteristics ...
متن کاملSteganalysis of JSteg algorithm using hypothesis testing theory
This paper investigates the statistical detection of JSteg steganography. The approach is based on a statistical model of discrete cosine transformation (DCT) coefficients challenging the usual assumption that among a subband all the coefficients are independent and identically distributed (i. i. d. ). The hidden information-detection problem is cast in the framework of hypothesis testing theor...
متن کاملA Novel Quantity Based on Clipping Statistics for Jsteg Steganalysis
Steganalysis is the art of detecting covert communication and has become an important research field, in which some of steganographic tools provide the function of embedding secret messages into JPEG images. To detect JPEG stego-images, we will identify a novel statistical quantity in this paper. In general, the JPEG decompression process performs color clipping in lots of pixels, and thus, mes...
متن کاملQuantitative steganalysis using rich models
In this paper, we propose a regression framework for steganalysis of digital images that utilizes the recently proposed rich models – high-dimensional statistical image descriptors that have been shown to substantially improve classical (binary) steganalysis. Our proposed system is based on gradient boosting and utilizes a steganalysis-specific variant of regression trees as base learners. The ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Information Forensics and Security
سال: 2010
ISSN: 1556-6013,1556-6021
DOI: 10.1109/tifs.2010.2056684