Worst case attack on quantization based data hiding

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1 Scopus citations

Abstract

Currently, most quantization based data hiding algorithms are built assuming specific distributions of attacks, such as additive white Gaussian noise (AWGN), uniform noise, and so on. In this paper, we prove that the worst case additive attack for quantization based data hiding is a 3δ function. We derive the expression for the probability of error (Pe) in terms of distortion compensation factor, α, and the attack distribution. By maximizing Pe with respect to the attack distribution, we get the optimal placement of the 3δ function. We then experimentally verify that the 3δ function is indeed the worst case attack for quantization based data hiding.

Original languageEnglish
Title of host publicationISM 2006 - 8th IEEE International Symposium on Multimedia
Pages679-684
Number of pages6
DOIs
StatePublished - 2006
EventISM 2006 - 8th IEEE International Symposium on Multimedia - San Diego, CA, United States
Duration: 11 Dec 200613 Dec 2006

Publication series

NameISM 2006 - 8th IEEE International Symposium on Multimedia

Conference

ConferenceISM 2006 - 8th IEEE International Symposium on Multimedia
Country/TerritoryUnited States
CitySan Diego, CA
Period11/12/0613/12/06

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