The goal of steganography is to embed a hidden message in a cover. Typical covers are audio and image files and use the least significant bits to hide the message. Steganalysis is the classification of files as stego-bearing or not. Many techniques exist using statistical analysis to classify files and rely on the fact that hidden messages tend to be hidden in the low order bits and this upsets the distribution of ones and zeros in a detectable way. This paper will explore using the Chi-Squared method of statistical analysis on database tables for detecting a hidden message embedded in the least significant bit of select attributes of the table. The authors explore the maximum length of a message that can be embedded in the low order bits and still avoid detection. The paper uses the Iris Plant database set and a subset of the Forest Cover dataset, both available from the UCI Data Repository.
展开▼
