학술논문

Optimal Cover Estimation Methods and Steganographic Payload Location
Document Type
Periodical
Author
Source
IEEE Transactions on Information Forensics and Security IEEE Trans.Inform.Forensic Secur. Information Forensics and Security, IEEE Transactions on. 6(4):1214-1222 Dec, 2011
Subject
Signal Processing and Analysis
Computing and Processing
Communication, Networking and Broadcast Technologies
Payloads
Viterbi algorithm
Hidden Markov models
Steganography
Computational modeling
Markov processes
Cover estimation
payload location
steganalysis
Viterbi decoding
Language
ISSN
1556-6013
1556-6021
Abstract
Cover estimation is an important part of steganalysis and has many applications. One such application is steganographic payload location using residuals, which is effective when a large number of stego images are available. In the ideal case when the cover images are available, we show that the expected number of stego images needed to perfectly locate all load-carrying pixels is approximately the logarithm of the payload size. In more practical settings when the cover images are not available, the accuracy of payload location depends primarily on the chosen cover estimation method. We present optimal, linear runtime algorithms for finding the most likely cover estimate given the stego image and experimentally demonstrate that they can be used to locate payload on both least-significant bit (LSB) replacement and LSB matching stego images. The algorithms can be extended to higher order statistical models of cover images.