Fast additive noise steganalysis

Jeremiah Joseph Harmsen; Kevin D. Bowers; William A. Pearlman

doi:10.1117/12.526003

22 June 2004 Fast additive noise steganalysis

Jeremiah Joseph Harmsen, Kevin D. Bowers, William A. Pearlman

Proceedings Volume 5306, Security, Steganography, and Watermarking of Multimedia Contents VI; (2004) https://doi.org/10.1117/12.526003
Event: Electronic Imaging 2004, 2004, San Jose, California, United States

Abstract

This work reduces the computational requirements of the additive noise steganalysis presented by Harmsen and Pearlman. The additive noise model assumes that the stegoimage is created by adding a pseudo-noise to a coverimage. This addition predictably alters the joint histogram of the image. In color images it has been shown that this alteration can be detected using a three-dimensional Fast Fourier Transform (FFT) of the histogram. As the computation of this transform is typically very intensive, a method to reduce the required processing is desirable. By considering the histogram between pairs of channels in RGB images, three separate two-dimensional FFTs are used in place of the original three-dimensional FFT. This method is shown to offer computational savings of approximately two orders of magnitude while only slightly decreasing classification accuracy.

Citation Download Citation

Jeremiah Joseph Harmsen, Kevin D. Bowers, and William A. Pearlman "Fast additive noise steganalysis", Proc. SPIE 5306, Security, Steganography, and Watermarking of Multimedia Contents VI, (22 June 2004); https://doi.org/10.1117/12.526003

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available