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Proceedings Paper

Optimally weighted least-squares steganalysis
Author(s): Andrew D. Ker
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Paper Abstract

Quantitative steganalysis aims to estimate the amount of payload in a stego object, and such estimators seem to arise naturally in steganalysis of Least Significant Bit (LSB) replacement in digital images. However, as with all steganalysis, the estimators are subject to errors, and their magnitude seems heavily dependent on properties of the cover. In very recent work we have given the first derivation of estimation error, for a certain method of steganalysis (the Least-Squares variant of Sample Pairs Analysis) of LSB replacement steganography in digital images. In this paper we make use of our theoretical results to find an improved estimator and detector. We also extend the theoretical analysis to another (more accurate) steganalysis estimator (Triples Analysis) and hence derive an improved version of that estimator too. Experimental results show that the new steganalyzers have improved accuracy, particularly in the difficult case of never-compressed covers.

Paper Details

Date Published: 2 March 2007
PDF: 16 pages
Proc. SPIE 6505, Security, Steganography, and Watermarking of Multimedia Contents IX, 650506 (2 March 2007); doi: 10.1117/12.704606
Show Author Affiliations
Andrew D. Ker, Oxford Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 6505:
Security, Steganography, and Watermarking of Multimedia Contents IX
Edward J. Delp; Ping Wah Wong, Editor(s)

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