document: Locating secret messages in images Steganography involves hiding messages in innocuous media such as images , while steganalysis is the field of detecting these secret messages . The ultimate goal of steganalysis is two-fold : making a binary classification of a file as stego-bearing or innocent , and secondly , locating the hidden message with an aim to extracting , sterilizing or manipulating it . Almost all steganalysis approaches ( known as attacks ) focus on the first of these two issues . In this paper , we explore the difficult related problem : given that we know an image file contains steganography , locate which pixels contain the message . We treat the hidden message location problem as outlier detection using probability\/energy measures of images motivated by the image restoration community . Pixels contributing the most to the energy calculations of an image are deemed outliers . Typically , of the top third of one percent of most energized pixels ( outliers ) , we find that 87 % are stego-bearing in color images and 61 % in grayscale images . In all image types only 1 % of all pixels are stego-bearing indicating our techniques provides a substantial lift over random guessing .
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