ICIP 2006, Atlanta, GA

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Paper Detail

Session:Steganography and Steganalysis
Time:Monday, October 9, 12:00 - 12:20
Presentation: Lecture
Topic: Security: Steganography and Steganalysis
Authors: Kenneth Sullivan; Mayachitra, Inc. 
 Kaushal Solanki; Mayachitra, Inc. 
 B. S. Manjunath; University of California, Santa Barbara 
 Upamanyu Madhow; University of California, Santa Barbara 
 Shivkumar Chandrasekaran; University of California, Santa Barbara 
Abstract: In steganography (the hiding of data into innocuous covers for secret communication) it is difficult to estimate how much data can be hidden while still remaining undetectable. To measure the inherent detectability of steganography, Cachin suggested the epsilon-secure measure, where epsilon is the Kullback Leibler (K-L) divergence between the cover distribution and the distribution after hiding. At zero divergence, an optimal statistical detector can do no better than guessing; the data is undetectable. The hider's key question then is, what hiding rate can be used while maintaining zero divergence? Though work has been done on the theoretical capacity of steganography, it is often difficult to use these results in practice. We therefore examine the limits of a practical scheme known to allow embedding with zero-divergence. This scheme is independent of the embedding algorithm and therefore can be generically applied to find an achievable secure hiding rate for arbitrary cover distributions.