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Image Steganalysis of Low Rate Embedding in Spatial Domain
, Ph.D. Dissertation Sharif University of Technology ; Ghaemmaghami, Shahrokh (Supervisor) ; Aref, Mohammad Reza (Co-Advisor)
Abstract
LSB embedding in spatial domain with very low rate can be easily performed and its detection in spite of many researches is very hard, while BOSS competition has been held to break an adaptive embedding algorithm with low rate. Thus, proposing powerful steganalyzer of very low rate in spatial domain is highly requested. In this thesis it has been tried to present some algorithms to detect secret message with very low rate in spatial domain using eigenvalues analysis and relative auto-correlation of image.First approach is based on the analysis of the eigenvalues of the cover correlation matrix that we used for the first time. Image partitioning, correlation function computation,...
Multi-dimensional correlation steganalysis
, Article MMSP 2011 - IEEE International Workshop on Multimedia Signal Processing ; 2011 ; 9781457714337 (ISBN) ; Diyanat, A ; Ghaemmaghami, S ; Aref, M. R ; Sharif University of Technology
2011
Abstract
Multi-dimensional spatial analysis of image pixels have not been much investigated for the steganalysis of the LSB Steganographic methods. Pixel distribution based steganalysis methods could be thwarted by intelligently compensating statistical characteristics of image pixels, as reported in several papers. Simple LSB replacement methods have been improved by introducing smarter LSB embedding approaches, e.g. LSB matching and LSB+ methods, but they are basically the same in the sense of the LSB alteration. A new analytical method to detect LSB stego images is proposed in this paper. Our approach is based on the relative locations of image pixels that are essentially changed in an LSB...